DETAILED ACTION
Disposition of Claims
Claims 1-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 56-57 are pending.
Examiner’s Note
All paragraph numbers (¶) throughout this office action, unless otherwise noted, are from the US PGPub of this application US20240269258A1, Published 08/15/2024.
Applicant is encouraged to utilize the new web-based Automated Interview Request (AIR) tool for submitting interview requests; more information can be found at https://www.uspto.gov/patent/laws-and-regulations/interview-practice.
Optional Authorization to Initiate Electronic Communications
The Applicant’s representative may wish to consider supplying a written authorization in response to this Office action to correspond with the Examiner via electronic mail (e-mail). This authorization is optional on the part of the Applicant’s representative, but it should be noted that the Examiner may not initiate nor respond to communications via electronic mail unless and until Applicant’s representative authorizes such communications in writing within the official record of the patent application. A sample authorization is available at MPEP § 502.03, part II. If Applicant’s representative chooses to provide this authorization, please ensure to include a valid e-mail address along with said authorization.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 04/21/2026, 09/15/2025, 07/03/2024, AND 04/05/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Notably, the disclosure statement filed lists a Search Report. The listing of the references cited in a Search Report itself is not considered to be an information disclosure statement (IDS) complying with 37 CFR 1.98. 37 CFR 1.98(a)(2) requires a legible copy of: (1) each foreign patent; (2) each publication or that portion which caused it to be listed; (3) for each cited pending U.S. application, the application specification including claims, and any drawing of the application, or that portion of the application which caused it to be listed including any claims directed to that portion, unless the cited pending U.S. application is stored in the Image File Wrapper (IFW) system; and (4) all other information, or that portion which caused it to be listed. In addition, each IDS must include a list of all patents, publications, applications, or other information submitted for consideration by the Office (see 37 CFR 1.98(a)(1) and (b)), and MPEP § 609.04(a), subsection I. states, "the list ... must be submitted on a separate paper." Therefore, the references cited in the Search Report have not been considered. Applicant is advised that the date of submission of any item of information or any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the IDS, including all "statement" requirements of 37 CFR 1.97(e). See MPEP § 609.05(a).
Note: If copies of the individual references cited on the Search Report are also cited separately on the IDS (and these references have not been lined-through) they have been considered.
Specification - Drawings
The drawings are objected to because Figs. 2-5 reference color in the drawings (see figure legend in specification.) Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification:
The patent or application file contains reference to at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
The abstract of the disclosure is objected to because of the use of implied phraseology (e.g. “Disclosed are multivalent…” and “…Also disclosed are…”). A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Objections
Claim 2 is objected to because of the following informalities: the definition of the abbreviation “mRNA” is not provided. For clarity, it is requested that the first recitation of an abbreviation within a claim set be preceded by its full-length name (i.e. … messenger ribonucleic acid (mRNA) molecule...).
Appropriate correction is required.
Claim 56 is objected to because of the following informalities: there is an item (b) recited (line 4) without a corresponding item (a) preceding it.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b); Second Paragraph
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 and 56 and dependent claims 2-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 57 thereof are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 56 provide for “one or more machine learning influenza virus HA having a molecular sequence identified or designed from a machine learning model, or one or more ribonucleic acid molecules encoding the one or more machine learning influenza virus HA, wherein the one or more machine learning influenza virus HA are selected from an H1 HA, an H3 HA, an HA from a B/Victoria lineage, an HA from a B/Yamagata lineage, or a combination thereof.” However, the limitation of a sequence “designed from a machine learning model” does not have an objective structural boundary so one of skill in the art can determine if said sequence was “designed from a machine learning model” or not. The claims do not identify any particular HA sequences or a sequence-identity threshold, it does not identify any mutations or combination of mutations that are made to a “base” sequence, it does not define wild-type/natural sequences that can be included or should be excluded, and it does not define any other measurable property that allows a skilled artisan to identify a “machine learning model” designed HA from one that is not “machine designed”. Further, no specific algorithms, datasets, or model types are claimed that allow a skilled artisan to know how said “machine designed” HA was designed. The specification does not cure this deficiency, as ¶[0119] notes that “any machine-learning algorithm may be used” and the definition of “machine learning” at ¶[0056] does not provide a structural or objective boundary as to how to determine said HA was modeled using “machine learning”.
Additionally, claims 1 and 56 use the term “standard of care influenza virus strain”. At ¶[0066] of the specification, “standard of care strain” is defined as an influenza strain included in the seasonal vaccine preparations. It notes that these strains may be historical, current, or future standard of care (SOC) strains. However, claims 1 and 56 fail to identify which World Health Organization (WHO) recommendation controls what is selected, as the claims fail to identify any particular influenza season, the specific hemisphere (e.g. northern or southern hemisphere SOC strain), whether the historical recommendation is sufficient, whether the exact strain must be chosen or a “similar” or “like” variant is sufficient, or when the recommendation from the WHO must be made (e.g. made as of the filing date, or applicable to any future recommendation, etc.) MPEP §2173.04 states that “A broad claim is not indefinite merely because it encompasses a wide scope of subject matter provided the scope is clearly defined. But a claim is indefinite when the boundaries of the protected subject matter are not clearly delineated and the scope is unclear. For example, a genus claim that covers multiple species is broad, but is not indefinite because of its breadth, which is otherwise clear. But a genus claim that could be interpreted in such a way that it is not clear which species are covered would be indefinite (e.g., because there is more than one reasonable interpretation of what species are included in the claim).”[emphasis added] Because it is unclear as to the entire scope of what is being claimed, as future, unselected strains may become part of the claim, the scope of what is, and is not included, is unclear. Additionally, updated WHO recommendations are that B/Yamagata lineage antigens are no longer warranted in seasonal influenza vaccines and the B/Yamagata within vaccines moving forwards remains B/Phuket/3073/2013-like virus (World Health Organization. “Recommendations announced for influenza vaccine composition for the 2026 southern hemisphere influenza season.” 26 Sept 2025.) Therefore, it is unclear if any prior selected influenza strain remains within the scope of the claim indefinitely, whether a strain selected by the WHO after the filing date enters the scope of the claim upon its selection in the future, and whether the exact WHO reference strain or a “like” antigenically similar strain is encompassed, which prevents a skilled artisan from identifying the scope of the genus claimed at the time of filing.
Additionally, claims 1 and 56 claim “wherein the one or more machine learning influenza virus HA are selected from an H1 HA, an H3 HA, an HA from a B/Victoria lineage, an HA from a B/Yamagata lineage, or a combination thereof.” Applicant is requested to clarify if the “or a combination thereof” is intended to refer to a combination of separate influenza virus HAs in part (e) or if the “combination thereof” refers to a hybrid or chimeric influenza virus HA comprising portions of two or more of the recited HA in the Markush group of part (e).
Since a skilled artisan would not be reasonably apprised as to the metes and bounds of the claimed invention, instant Claims 1 and 56 are rejected on the grounds of being indefinite. Claims 2-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 57 are also rejected since they depend from claim 1 or 56, but do not remedy these deficiencies of claim(s) 1 or 56.
Claims 2-3 and 43 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 refers to “the ribonucleic acid molecule”. However, there are multiple “ribonucleic acid molecules” recited in claim 1, and it is unclear if this refers to one, more than one, or all of said ribonucleic acid molecules recited in claim 1. Claims 3 and 43 are rejected for similar reasoning.
For at least these reasons, the metes and bounds of claims 2-3 and 43 are unclear.
Claim 4 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 4 recites the limitation "the molecular sequence" in line 2. The antecedence for this appears to be the “molecular sequence” of part (e) in claim 1. However, an “influenza virus HA” is already interpreted a protein having an amino acid sequence, whereas a nucleic acid sequence would encode the HA. It is unclear whether claim 4 is intended to further define the molecular sequence of the HA of part (e) itself, a nucleic acid encoding said HA, or both.
For at least these reasons, the metes and bounds of claim 4 are unclear.
Claims 5-6 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 provides the limitation of the influenza HA being a “wild type influenza A molecular sequence”, while claim 6 provides the limitation of wherein the machine learning influenza virus HA comprise a non-wild type influenza HA molecular sequence. However, no frame-of-reference has been provided for any base sequence, so it is unclear how said claimed sequence is determined to be “wild type” or “non-wild type”. Further, the specification and claim are not clear as to whether or not the negative limitation in claim 6 (e.g. “non-wild type influenza virus HA molecular sequence”) excludes all naturally occurring variants or only the sequence of a selected reference strain.
For at least these reasons, the metes and bounds of claims 5 and 6 are unclear.
Claim 9 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 9 is drawn to the immunogenic composition according to claim 1, comprising a ribonucleic acid molecule encoding at least one of the one or more machine learning influenza virus HA. From the wording of the claim, it is unclear if this is meant to be further limiting on part (e) of claim 1, or if this is an additional item within the composition with respect to items (a)-(e).
For at least these reasons, the metes and bounds of claim 9 unclear.
Claims 11, 17, and 26 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 11 is drawn to “wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H3 HA, and wherein the fifth influenza H3 HA enhances or broadens a protective immune response induced by the second influenza H3 HA.” The terms “broadens” and “enhances” in claim 11 are relative terms which render the claim indefinite. The terms “broadens” and “enhances” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The specification defines a “protective immune response” (¶[0068]) as “an immune response that protects a subject from infection (prevents infection or prevents the development of disease associated with infection) or reduces the symptoms of infection (for instance an infection by an influenza virus).” It also states that biological responses may be compared to determine whether a composition enhances or broadens an immune response relative to a composition lacking the one or more machine-learning HAs (¶[0155]). The specification provides examples of assays which may be used, such as HAI assays, ELISAs, antibody forensics assays, and viral neutralization assays (¶[0156-0158]). However, the claims do not specify or note which assay should be used, the subject or animal model to be evaluated, the influenza virus strains to be included/excluded in the assay, the required magnitude of any increase (or if said increase must be statistically significant), or the minimum additional strain coverage to be considered a “broadened” response. While the specification notes multiple assays that may be used, the specification also notes the limitations of these assays, and that the results of said assays are not necessarily linearly related (¶[0157]).
Claims 17 and 26 are rejected for similar reasoning. Claim 26 is additionally indefinite because from the wording of the claim, it is unclear whether the recited “wherein” characteristics are alternative embodiments/limitations or are cumulative requirements.
For at least these reasons, the metes and bounds of claims 11, 17, and 26 are unclear.
Claim 24 and dependent claims 25-28 thereof are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 24 is drawn to the immunogenic composition according to claim 1, further comprising a sixth influenza virus HA. However, claim 1 clearly recites four HA (items (a)-(d)) and then in item (e), there can be one or more HA. Therefore, reciting a “further comprising a sixth influenza virus HA” in claim 24 is confusing, because it is unclear whether the sixth HA is intended to be an additional HA distinct from the one or more machine learning HA of part (e), a second member of the plurality of machine learning HA of part (e), or an otherwise unrelated but additional HA. One suggestion is to have claim 24 depend upon one of the claims that clearly recite a fifth HA. Another suggestion is to amend this claim so that it recites a part (f) and notes that it is an additional HA within the composition that is distinct from those HA listed in parts (a)-(e) of claim 1.
For at least these reasons, claim 24 is rejected on the grounds of being indefinite. Claims 25-28 are also rejected for depending upon claim 24, but not further clarifying the metes and bounds of claim 24.
Claim 26 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 26 depends upon claim 25, and recites “wherein the sixth influenza H1 HA is antigenically dissimilar than the first influenza H1 HA, wherein the sixth influenza H1 HA enhances a protective immune response induced by the first influenza H1 HA, wherein the sixth influenza H1 HA broadens a protective immune response induced by the first influenza H1 HA, wherein the sixth influenza H1 HA is from a different clade than the first influenza H1 HA, wherein the sixth influenza H1 HA is from a same clade as the first influenza H1 HA, or wherein the sixth influenza H1 HA is antigenically similar to the first influenza H1 HA.” From the wording of the claim, it is unclear whether the recited characteristics are intended to be cumulative requirements, alternative limitations, or a combination thereof. As written, the claim seems to require that the sixth H1 HA be both antigenically similar and dissimilar from the first influenza H1 HA, and both a different and same clade. From how this claim is drafted, it is unclear if whether the first five limitations recited in the claim are cumulative and only the last/final limitation is in the alternative, or whether each listed characteristic is intended to be an alternative option.
For at least these reasons, the metes and bounds of claim 26 are unclear.
Claim 29 and dependent claims 30-31 thereof are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 29 is drawn to the immunogenic composition according to claim 1, wherein the machine learning model is trained to predict a biological response (claim 29), wherein the biological response is a human, ferret, or mouse biological response (claim 30), and wherein the biological response comprises a hemagglutinin inhibition assay (HAI), antibody forensics (AF), or neutralization assay (claim 31). However, the term “biological response” is unclear and not defined by the claim or the specification. For instance, the specification notes that the biological response may be detected by “hemagglutinin inhibition assay (HAI), antibody forensics (AF), or neutralization assay”(¶[0019]) but it is unclear from the specification and claims what biological response is being predicted and dependent claim 31 only provides the tools for measuring the response, but does not clarify what said response should be. Further, it is unclear if the biological response is to the HA antigen, to a specific influenza strain/isolate, or to the entire composition. Even further, it is unclear if the “biological response” must be of a certain strength or pass a certain threshold to be considered a “positive” or “negative” response.
For at least these reasons, claim 29 is rejected on the grounds of being indefinite. Claims 30-31 are also rejected for depending upon claim 29, but not further clarifying the metes and bounds of claim 29.
Claim 57 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 57 depends upon claim 56, and is drawn to wherein the composition is “comprising:
(a) a first influenza virus hemagglutinin (HA) wherein the first influenza virus HA is an H1 HA from a first standard of care influenza virus strain, or a first ribonucleic acid molecule encoding the first influenza virus H1 HA;
(b) a second influenza virus HA wherein the second influenza virus HA is an H3 HA from a second standard of care influenza virus strain, or a second ribonucleic acid molecule encoding the second influenza virus H3 HA;
(c) a third influenza virus HA wherein the third influenza virus HA is from a third standard of care influenza virus strain from the B/Victoria lineage, or a third ribonucleic acid molecule encoding the third influenza virus HA from the B/Victoria lineage; and
(d) the one or more machine learning influenza virus HA having a molecular sequence identified or designed from a machine learning model, or one or more ribonucleic acid molecules encoding the one or more machine learning influenza virus HA.” However, from the wording of the claim, and the presence of (b) (and supposedly a missing (a) in claim 56), it is unclear if the limitations in claim 57 are meant to further limit claim 56 by exemplifying the genera of claim 56, or if the limitations in claim 57 are further additional items in the composition of claim 56 (e.g. wherein the composition further comprises (a) – (d)). For instance, if the former is true, it is suggested that it be clarified that there are three HAs from standard of care (SOC) influenza virus strains and one machine learning HA strain, and that said three SOC HAs and one machine learning HA are then listed using different listing identifiers other than (a), (b), (c), and (d) (e.g. (i)-(iv) can be used.) Additionally, part (d) appears to be expanding the scope of the claim of claim 56 or is missing a further limiting identifier (e.g. claim 56 noted the machine learning HA was H1, H3, B/Victoria, or B/Yamagata, but claim 57 part (d) appears to not further identify the specific identity of said machine learning HA.)
For at least these reasons, the metes and bounds of claim 57 are unclear.
Claim Rejections - 35 USC § 112(d); Fourth Paragraph
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 57 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. As set forth supra in the 35 USC 112b rejection, part (d) of claim 57 appears to not further limit the Markush group of claim 56 part (b). Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.
Claim 1 is drawn to an immunogenic composition, comprising:
(a) a first influenza virus hemagglutinin (HA), wherein the first influenza virus HA is an H1 HA from a first standard of care influenza virus strain, or a first ribonucleic acid molecule encoding the first influenza virus H1 HA;
(b) a second influenza virus HA, wherein the second influenza virus HA is an H3 HA from a second standard of care influenza virus strain, or a second ribonucleic acid molecule encoding the second influenza virus H3 HA;
(c) a third influenza virus HA, wherein the third influenza virus HA is from a third standard of care influenza virus strain from the B/Victoria lineage, or a third ribonucleic acid molecule encoding the third influenza virus HA from the B/Victoria lineage;
(d) a fourth influenza virus HA wherein the fourth influenza virus HA is from a fourth standard of care influenza virus strain from the B/Yamagata lineage, or a fourth ribonucleic acid molecule encoding the fourth influenza virus HA from the B/Yamagata lineage; and
(e) one or more machine learning influenza virus HA having a molecular sequence identified or designed from a machine learning model, or one or more ribonucleic acid molecules encoding the one or more machine learning influenza virus HA, wherein the one or more machine learning influenza virus HA are selected from: an H1 HA, an H3 HA, an HA from a B/Victoria lineage, an HA from a B/Yamagata lineage, or a combination thereof.
Further limitations on the immunogenic composition according to claim 1 are wherein the ribonucleic acid molecule is a messenger ribonucleic acid (mRNA) molecule (claim 2); wherein the ribonucleic acid molecule is encapsulated in a lipid nanoparticle (LNP)(claim 3); wherein the molecular sequence of part (e) is an amino acid sequence or a nucleic acid sequence (claim 4); wherein the one or more machine learning influenza virus HA comprise a wild type influenza virus HA molecular sequence (claim 5); wherein the one or more machine learning influenza virus HA comprise a non- wild type influenza virus HA molecular sequence (claim 6); wherein the one or more machine learning influenza virus HA is a recombinant influenza virus HA (claim 7), wherein each of the recombinant influenza virus HA is produced by a baculovirus expression system in cultured insect cells (claim 35); wherein the one or more machine learning influenza virus HA is present in an inactivated influenza virus (claim 8); comprising a ribonucleic acid molecule encoding at least one of the one or more machine learning influenza virus HA (claim 9); wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H3 HA, and wherein the fifth influenza H3 HA is antigenically dissimilar than the second influenza H3 HA or wherein the fifth influenza H3 HA is from a different clade than the second influenza H3 HA (claim 10); wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H3 HA, and wherein the fifth influenza H3 HA enhances or broadens a protective immune response induced by the second influenza H3 HA (claim 11); wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H3 HA, and wherein the fifth influenza H3 HA is antigenically similar to the second influenza H3 HA or wherein the fifth influenza H3 HA is from a same clade as the second influenza H3 HA (claim 14); wherein the one or more machine learning influenza virus HA is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H1 HA, and wherein the fifth influenza H1 HA is antigenically dissimilar than the first influenza H1 HA or wherein the fifth influenza H1 HA is from a different clade than the first influenza H1 HA (claim 16); wherein the one or more machine learning influenza virus HA is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H1 HA, and wherein the fifth influenza H1 HA enhances or broadens a protective immune response induced by the first influenza H1 HA (claim 17); wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H1 HA, and wherein the fifth influenza H1 HA is antigenically similar to the first influenza H1 HA or wherein the fifth influenza H1 HA is from a same clade as the first influenza H1 HA (claim 20); wherein the one or more machine learning influenza virus HAs is a fifth influenza virus HA, wherein the fifth influenza virus HA is an H3 HA from the 3C.2A clade or the 3C.3A clade (claim 22); further comprising a sixth influenza virus HA (claim 24), wherein the sixth influenza virus HA is an H1 HA having a molecular sequence identified or designed from a machine learning model, or a ribonucleic acid molecule encoding the sixth influenza virus HA (claim 25), wherein the sixth influenza H1 HA is antigenically dissimilar than the first influenza H1 HA, wherein the sixth influenza H1 HA enhances a protective immune response induced by the first influenza H1 HA, wherein the sixth influenza H1 HA broadens a protective immune response induced by the first influenza H1 HA, wherein the sixth influenza H1 HA is from a different clade than the first influenza H1 HA, wherein the sixth influenza H1 HA is from a same clade as the first influenza H1 HA, or wherein the sixth influenza H1 HA is antigenically similar to the first influenza H1 HA (claim 26), further comprising a seventh influenza virus HA from the B/Victoria lineage having a molecular sequence identified or designed from a machine learning model, or a ribonucleic acid molecule encoding the seventh influenza virus HA (claim 27), further comprising an eighth influenza virus HA from the B/Yamagata lineage having a molecular sequence identified or designed from a machine learning model, or a ribonucleic acid molecule encoding the eighth influenza virus HA (claim 28); wherein the machine learning model is trained to predict a biological response (claim 29), wherein the biological response is a human, ferret, or mouse biological response (claim 30), and wherein the biological response comprises a hemagglutinin inhibition assay (HAI), antibody forensics (AF), or neutralization assay (claim 31); wherein each of the first, second, third, and fourth influenza virus HA is a recombinant influenza virus HA (claim 32); wherein each of the first, second, third, and fourth influenza virus HA is present in an inactivated influenza virus (claim 33); comprising the first, second, third, and fourth influenza virus HA as ribonucleic acid molecules (claim 34); wherein the first influenza virus HA is an H1 HA from an H1N1 influenza virus strain and the second influenza virus HA is an H3 HA from an H3N2 influenza virus strain (claim 36); wherein the composition further comprises an adjuvant (claim 37), wherein the adjuvant comprises a squalene-in-water adjuvant or a liposome-based adjuvant (claim 38); wherein each ribonucleic acid molecule comprises one or more modified nucleotides (claim 41); wherein the composition is formulated for intramuscular injection (claim 42); wherein the ribonucleic acid molecule is encapsulated in an LNP comprising a cationic lipid, a PEGylated lipid, a cholesterol-based lipid, and a helper lipid (claim 43); and a vaccine composition comprising the immunogenic composition according to claim 1 (claim 54).
Claim 44 is drawn to a method of immunizing a subject against influenza virus, the method comprising administering to the subject an immunologically effective amount of the immunogenic composition of claim 1.
Claim 52 is drawn to a method of reducing one or more symptoms of influenza virus infection, the method comprising administering to a subject a prophylactically effective amount of the immunogenic composition of claim 1.
Claim 56 is drawn to an immunogenic composition, comprising:
(a) at least three or at least four influenza virus hemagglutinins (HAs) from standard of care influenza virus strains, or at least three or at least 4 ribonucleic acid molecule encoding the influenza virus HAs; and
(b) one or more machine learning influenza virus HA having a molecular sequence identified or designed from a machine learning model, or one or more ribonucleic acid molecules encoding the one or more machine learning influenza virus HA,
wherein the one or more machine learning influenza virus HA are selected from an H1 HA, an H3 HA, an HA from a B/Victoria lineage, an HA from a B/Yamagata lineage, or a combination thereof.
Further limitations on the immunogenic composition of claim 56 are wherein the composition comprises three standard of care HAs and one machine learning HA, wherein said HAs are as follows:
wherein the standard of care HAs are:
(i) a first influenza virus hemagglutinin (HA) wherein the first influenza virus HA is an H1 HA from a first standard of care influenza virus strain, or a first ribonucleic acid molecule encoding the first influenza virus H1 HA;
(ii) a second influenza virus HA wherein the second influenza virus HA is an H3 HA from a second standard of care influenza virus strain, or a second ribonucleic acid molecule encoding the second influenza virus H3 HA;
(iii) a third influenza virus HA wherein the third influenza virus HA is from a third standard of care influenza virus strain from the B/Victoria lineage, or a third ribonucleic acid molecule encoding the third influenza virus HA from the B/Victoria lineage; and
wherein the one or more machine learning influenza virus HA having a molecular sequence identified or designed from a machine learning model, or one or more ribonucleic acid molecules encoding the one or more machine learning influenza virus HA (claim 57).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 2, 4, 5, 7, 9-10, 14, 16, 20, 22, 24-32, 34, 36, 42, 54, and 56-57 are rejected under 35 U.S.C. 101 because the claimed invention is directed to compositions comprising naturally-occurring influenza HA without significantly more. The claims recite an immunogenic composition comprising five (a-e) influenza HA molecules or ribonucleic acids encoding said influenza HA molecules, wherein said influenza HA ribonucleic acids or proteins are naturally occurring sequences/proteins. This judicial exception is not integrated into a practical application because the full eligibility analysis does not point to said composition being significantly more than the judicial exception. The claims are within a statutory composition of matter (step 1: yes), and under the broadest reasonable interpretation, the composition encompasses an embodiment in which each of the five HA are naturally occurring. Dependent claim 5 confirms that the “machine learning influenza virus HA” may be naturally occurring, and simply because a sequence was identified in an algorithm does not make said sequence “non-natural”. The analysis cannot be streamlined, so we move on to step 2. The composition is therefore a combination of nature-based products, and the analysis as to whether or not said composition is markedly different is applied to the resulting combination of products, not each naturally-occurring sequence in isolation. While the claim requires that the composition be “immunogenic”, there is nothing in the composition to establish this immunogenic status as being protective or of a specific type/strength (e.g. synergistic immunogenicity), and it is well-known that influenza HA are “immunogenic” on their own (Step 2A, Prong One: Yes). The analysis then moves to if the exception is integrated into a practical application, and the claim is generically recited as a “composition” that is “immunogenic” and fails to recite any particular administration step, any specific treatment step/modality, a required dosage to elicit a specific type of immune response, or a required synergistic immune response elicited by the claimed combination (Step 2A, Prong Two: No.) Turning to step 2B, the claim does not recite additional elements that amount to significantly more than the nature-based HA combination, as there is no requirement that any of the HA sequences are non-naturally occurring (e.g. fusion proteins of HA with heterologous tags or signal sequences) or that the composition comprise additional components that change said naturally-occurring HA (e.g. presence of adjuvants.) The limitation of “machine learning” for step (e) fails to impart a functional distinction from naturally occurring influenza HA (see 35 USC 112b rejection supra). Similarly, collecting naturally occurring HAs or HA-encoding RNA sequences into an immunogenic or vaccine composition without requiring a changed characteristic caused by the combination does not provide an inventive concept beyond the product-of-nature exception (Step 2B: No.) Taken as a whole, the claims are not drawn to patent-eligible subject matter.
One suggestion to overcome this rejection is to incorporate limitations from claims not included in this rejection into the independent claims. Another suggestion is to amend the claims to require a structural or functional characteristic that distinguishes the claimed combination from the naturally occurring counterparts (e.g. non-naturally occurring HA sequences, heterologous HA fusion proteins, inclusion of adjuvants in the composition, inclusion of LNPs in the composition, etc.) Applicant is also free to present persuasive evidence that the claims are patent eligible.
Claim Rejections - 35 USC § 112(a); First Paragraph
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 56-57 are rejected under 35 U.S.C. 112(a), or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
The written description requirement is separate and distinct from the enablement requirement. To satisfy the written description requirement, the specification must reasonably convey to one skilled in the relevant art that the inventor had possession of the claimed invention as of the filing date. Possession may be shown by a description of the complete structure of the claimed invention, a representative number of species falling within the scope of a claimed genus, or relevant identifying characteristics sufficient to show that the inventor had possession of the claimed subject matter.
Claims 1-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 56-57 recite an immunogenic composition comprising H1, H3, B/Victoria lineage, and B/Yamagata lineage influenza virus HAs from standard of care (SOC) influenza virus strains, or ribonucleic acid molecules encoding said HAs, together with one or more additional machine-learning influenza virus HAs, or ribonucleic acid molecules encoding said machine-learning HAs. The additional machine learning HAs may be selected from H1, H3, B/Victoria lineage, and B/Yamagata lineage, or a combination thereof. The specification describes the general concept of supplementing a convention quadrivalent influenza vaccine with one or more additional HAs identified or designed using a machine-learning model(¶[0009-0025]). For said learning model, see WO 2021/080990 A1, and WO 2021/080999 A1 (BOTH CITED IN IDS; ¶[0056]). The specification further states that a SOC strain may be a “historical standard of care strain, a current standard of care strain or a future standard of care strain.”(¶[0066]) The disclosed HAs may be wild-type or non-wild-type HAs, may be derived from seasonal or pandemic strains, and may be provided in “any other form known in the art.”(¶[0082]).
The specification also describes systems and methods that may be used to identify or design candidate antigens. The specification states that “any machine learning algorithm may be used.” (¶[0119]). The disclosed systems may use feature extraction, dimensionality reduction, temporal sequence data, recurrent neural networks, deep neural networks, and models trained to predict biological responses (¶[0119-0131][0147-0154]).
The working examples provided for in the specification are narrower than these envisioned embodiments. Example 1 evaluates administration of single H3N2 inactivated viruses or cocktails of two H3N2 inactivated viruses in naïve ferrets. The tested viruses were selected from 3C.2A and 3C.3A clades. The reported results concern the effect of combining selected H3 HAs on neutralizing antibody breadth against an H3 readout panel (¶[0307-0312]; Table 1). Example 2 evaluates a quadrivalent mRNA influenza vaccine and pentavalent mRNA formulations containing one additional H3 HA antigen. The quadrivalent formulation contained mRNAs encoding HAs from 2021-2022 northern hemisphere WHO standard of care (WHO SOC) strains (H1, H3, BVic, and BYam) (specifically from strains A/Wisconsin/588/2019 (H1N1), A/Tasmania/503/2020 (H3N2), B/Washington/02/2019 ,(Victoria lineage) and B/Phuket/3073/2013 (Yamagata lineage)). The pentavalent formulation included those HA and one additional HA selected via machine learning to provide clade H3C.2A protection (specifically, wild-type A/Norway/2629/2015), with the HA mRNA from each strain present in an amount of 15 μg (¶[0315-0324]). The reported results concern the selected H3C.2A and H3C.3A embodiments (¶[0313-0337]; Tables 2-4.)
However, the scope of the claims is not limited to the embodiments described in the specification. The claims broadly encompass any H1, H3, B/Victoria, and B/Yamagata with any combination of at least one machine learning HA, and the scope of claim 1 and further dependent claims includes wild-type sequences selected from natural isolates and non-wild type sequences generated by any model. The claims are not limited to only the disclosed 2021-2022 Northern Hemisphere SOC strains, the disclosed H3 clades, the tested formulations, or the specific sequences evaluated in the ferret studies.
The specification does not describe a sufficient number of species representative of the claimed scope. The specification does not identify an exemplified machine learning H1, B/Yamagata, or B/Victoria HA, and the specification fails to describe any further representative compositions containing any other SOC strains from any other seasons or hemispheres. Instead, the specification identifies only the desired antigen categories and states that an algorithm may be used to select or design additional candidates.
The specification also does not describe structural features common to the claimed genus which would allow one skilled in the art to recognize which additional species fall within the scope of the claimed invention. Instead, one skilled in the art would be required to select additional H1, H3, B/Victoria, and B/Yamagata sequences that are either SOC or identified by an algorithm which were not described in the specification or examples and determine whether those additional embodiments satisfy the recited limitations. Furthermore, the limitation of “having a molecular sequence identified or designed from a machine learning model” identifies the manner in which a candidate may be obtained, but it fails to identify a common amino acid or nucleic acid sequence, a conserved structural feature, or any other characteristic that distinguishes the claimed group of “machine identified” HAs from other HAs. The dependent claims fail to cure this deficiency, as they encompass a variety of wild-type or computationally optimized HA sequences. The specification fails to describe a sufficient number of HAs falling within the claimed genera by sequence or other structural characteristics sufficient to show possession of these genera.
Furthermore, the claimed HA are defined, at least in part, by the recited function of the ability to enhance or broaden protective immune responses. However, the specification does not establish a correlation between the disclosed structural features and the recited function sufficient to identify the additional HA antigens falling within the scope of the claim. The specification describes a limited number of quadrivalent and pentavalent compositions of HA antigens, but does not identify structural features common to the broader claimed genus which would allow one skilled in the art to recognize other members of the genus that would allow the generation of such responses, nor does the specification determine how one would measure or compare said responses. While the claims generically note the use of adjuvants, such as squalene-in-water or liposome-based adjuvants, it is unclear which adjuvants to use and whether or not said adjuvants are critical for achieving these enhanced or broadened immune responses. The specification notes that lipid nanoparticles (LNPs) may also be used, but it is unclear as to the exact composition of said LNPs, what cationic lipids/cholesterol-based lipids/PEGylated lipids/helper lipids can be used to generate the LNPs and in what weight ration each must be present; again, it is not clear if such LNPs are required for this functional protective response and which specific formulations of LNPs must be used to generate such functional response. The disclosure of the desired function, without a sufficient description of the claimed genus, does not demonstrate possession of the full scope of the claim.
The specification describes methods of administering the compositions to naïve ferrets in the examples, and notes that the target organisms may be rodents, mice, rats, rabbits, ferrets, monkeys, dogs, cats, sheep, cattle, primates, humans, and/or pigs (¶[0044][0067]) that receive the compositions of the specification. The claimed methods recite administering the claimed compositions, raising an immune response, preventing or treating influenza-associated disease, reducing symptoms, or using the compositions as vaccines, but the specification fails to provide representative treatment examples across the full scope of the claimed genera of HA antigens and compositions thereof to the species thereof. The additional method limitations fail to provide written descriptive support for the broader compositions used in the methods or the claimed methods in general.
Accordingly, the disclosure does not reasonably convey to one skilled in the art that the inventor had possession of the full scope of the subject matter recited in the claims at the time the application was filed.
Claims 1-11, 14, 16-17, 20, 22, 24-38, 41-44, 52, 54, and 56-57 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification, while being enabling for specific quadrivalent and pentavalent influenza virus HA mRNA/LNP formulations comprising specified 2021-22 Northern Hemisphere WO SOC HAs and select additional H3 HAs evaluated in naïve ferrets, does not reasonably provide enablement for the broader scope of multivalent influenza HA compositions and methods encompassed by the claims. The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the invention commensurate in scope with these claims.
The legal considerations that govern enablement determinations pertaining to undue experimentation have been set forth in In re Wands, 858 F.2d 731, 737, 8 USPQ2d 1400, 1404 (Fed. Cir. 1988). The factors to be considered include: (1) the breadth of the claims; (2) the nature of the invention; (3) the state of the prior art; (4) the level of one of ordinary skill; (5) the level of predictability in the art; (6) the amount of direction provided by the inventor; (7) the existence of working examples; and (8) the quantity of experimentation needed to make or use the invention based on the content of the disclosure. The factors are considered as a whole in determining whether any necessary experimentation would have been undue.
Nature of the invention and breadth of the claims. The claimed invention is directed to multivalent immunogenic compositions comprising HAs from SOC influenza strains and one or more additional machine-learning influenza virus HAs, or ribonucleic acids encoding any of said HAs. The claims require at least one each of H1 HA, H3 HA, B/Victoria HA, and B/Yamagata HA from an SOC strain, and the machine learning must be at least one HA from one or more of those same four influenza groups. The claims are further drawn to vaccines comprising said compositions, said compositions comprising further elements, such as adjuvants and LNPs, and methods of administering said compositions in a subject in need thereof to elicit therapeutic or prophylactic immune responses against influenza virus.
The claims are drawn to the HA antigens being either proteins or ribonucleic acids, but do not limit either to be of any specific embodiment. For instance, the proteins may be full-length or fragments thereof, or may be present within whole virions. Likewise, the ribonucleic acid does not have to be isolated or purified RNA, chemically modified RNA, non-replicating RNA, or RNA encapsulated in a lipid nanoparticle (LNP).
The specification describes a limited set of tested embodiments, as described supra with the written description rejection. Example 1 evaluates administration of H3N2 virus mixtures in naïve ferrets to assess antibody responses elicited by antigenically similar and antigenically dissimilar H3 combinations, wherein the tested combinations involve strains from the 3C.2A and 3C.3A clades (¶[0307-0312]). Example 2 evaluates quadrivalent and pentavalent influenza vaccines in naïve ferrets. The pentavalent formulations comprise mRNAs encoding the four 2021-2022 Northern Hemisphere WHO SOC HA’s as noted supra, together with an additional H3 HA. The added H3 components include the wild-type A/Norway/2629/2015 strain selected using machine learning, the non-wild-type A/Design/H3S25/2019 sequence selected using machine learning, the wild-type A/Washington/526/2019 strain selected using machine learning, and the prior WHO SOC A/Kansas/14/2017 strain. The mRNAs were monoencapsulated by subtype in unidentified LNPs and combined into a single formulation before immunization. Ferrets received 2 intramuscular (I.M.) doses 21 days apart, and humoral responses were evaluated using a microneutralization assay on d49 (¶[0315-0337]).
However, the claims are not limited to the disclosed embodiments. The claims also encompass non-2021-2022 Northern Hemisphere SOCs, and cover any wild-type or computationally generated/optimized HA sequence (wherein the machine HA is identified/generated using any algorithm) from the claimed influenza subtypes, in either protein or any ribonucleic acid format, or in any inactivated influenza virus format, with any adjuvant or any LNP formulation. The methods are not limited to delivery to a single species, nor are they directed to any specific type of anti-influenza immune response (e.g. homotypic or heterotypic). The claimed scope therefore extends beyond the embodiments described in the specification.
State of the prior art and predictability of the art. At the time the application was filed, it was known that influenza virus HA selection for vaccine compositions was not a predictable exercise. Chan et. al. (Chan MCW, et. al. Emerg Infect Dis. 2018 Oct;24(10):1825-1834.) reported that continuous evolution of influenza surface proteins produces antigenic drift and allows escape from immunity induced by earlier infection or immunization. Chan noted that H3N2 exhibited “continuous unidirectional evolution” while influenza B variants followed multiple directions and co-circulated for a median of six years before displacement. The study by Chan also reported frequent mismatch between circulating strains and WHO-recommended vaccine strains. Chan noted that vaccine matching is not merely by sequence comparison, and typically was based on hemagglutination inhibition (HI) assay, but that using amino acid sequence of HA to infer vaccine matching was useful because genetic and antigenic characteristics of influenza viruses display remarkable correspondence, and both carry a strong correlation with vaccine effectiveness. H3N2 variants, however, had progressively reduced avidity in the HI assays, making the results more difficult to interpret, but that a molecular mismatch does not exclude potential cross-protection. The teachings of Chan therefore show that the art recognized HA sequence, assay output, circulating strains, and protective responses were related, but not necessarily interchangeable.
Ciaramella et. al. (US20180311336A1; CITED IN IDS) teaches broad-spectrum influenza mRNA vaccines, consensus HA sequences, multivalent antigen combinations, and delivery of said mRNA using specific LNP formulations. Ciaramella states that rapid HA evolution results in the “constant emergence of new strains”, which leaves host adaptive immunity only partially protective against new infections. Ciaramella describes consensus HA sequences generated from alignments of influenza sequences, and recognizes that mRNA vaccines may be arranged to seek cross-reactivity against seasonal and pandemic influenza virus strains. However, Ciaramella does not provide a universal rule for predicting which candidates will work. In mouse studies, Ciaramella showed that H1 consensus antigen mRNA detectably neutralized H1N1 PR8 challenge virus, while an H3 consensus antigen mRNA failed to show cross-reactive neutralization response to said H1N1 viral challenge. Ciaramella also states that LNP formulation may be influenced by, but not limited to, the selection of the cationic lipid component, the degree of cationic lipid saturation, the nature of the PEGylation, ratio of all components, and biophysical parameters such as size (¶[0343]). Ciaramella teaches that the tools for testing and preparing candidates was known, but it does not show that antigen performance could be predicted across influenza subtypes, sequence designs, delivery formats, and combinations without extensive empirical testing.
Nabel et. al. (WO2019195284A1) likewise teaches antigenic multivalent influenza HA compositions. Nabel states that vaccine strains must be picked half a year or more before flu season and often suffer from mismatch due to genetic shift and drift and the emergence of new strains. Even when properly matched, current vaccines only have a 50-60% efficacy. Nabel further explains that most neutralizing HA antibodies wherein the full-length HA is used as a subunit vaccine elicit antibodies against the highly variable HA head domain. Nabel does not treat multivalency as a result that may be assumed from antigen selection alone, and instead describes ferritin nanoparticles, immune-stimulatory moieties, different HA polypeptides, and animal testing of multivalent combinations against divergent challenge strains. Reference claims 19-25 expressly distinguish the composition, the second influenza-ferritin polypeptide, the antigen combination, and the method of eliciting an immune response. Nabel shows that candidate antigens and combinations could be prepared, but immunogenic breadth still remained a question that needed to be tested empirically.
Applicant’s own data are consistent with the state of the art. In Example 2, Group 1 included an added machine-learning selected H3 HA, but four ferrets failed to generate homologous neutralization titers against the B/Yamagata component, and the overall B/Yamagata titers were significantly lower than those observed for the quadrivalent control. Applicant states that the result may reflect a “technical issue with immunization or a strain-specific effect.” (¶[0329]). The data also show that simply adding more antigen did not reliably produce greater responses. Doubling the dose of the SOC H3 component did not increase the magnitude of the neutralizing antibody response in the tested dose range, and Ferrets receiving two H3s from the same 3C.2A clade generally “did not expand breadth into the 3C.3A space” (¶0334]) while formulations containing H3s from divergent clades showed at least an additive response (¶[0334-0337]).
The art was not sufficiently predictable to support extrapolation from the disclosed H3-added mRNA/LNP formulations in naïve ferrets to the full claimed scope. Accordingly, the results obtained using the disclosed embodiments would not have reasonably established that the broader claimed scope could be practiced without further experimentation.
Level of skill in the art. One skilled in the art would have been familiar with influenza virus strain surveillance, HA-sequence alignment, how to perform phylogenetic analyses of different HA sequences, how to perform recombinant protein manipulation and expression, inactivated influenza virus preparation/techniques, synthesis of RNA, generation of LNPs and encapsulation of RNA within said LNPs, and standard immunogenicity studies as they relate to influenza viruses and animal models. However, the existence of known methods for preparing and testing candidate embodiments does not establish that one skilled in the art would have known, without further experimentation, which additional machine learning HAs would remain immunogenic when combined with the four SOC HAs, especially in order to enhance or broaden a protective response, avoid interference, or provide protection in a human subject.
Working examples. The working examples have been described supra with respect to the 35 USC 112a written description rejection. Briefly, Example 1 evaluates inactivated virus H3 combinations in naïve ferrets, while Example 2 evaluates quadrivalent or pentavalent mRNA/LNP vaccine formulations. The examples support that selected H3 combinations may produce additive antibody responses and broader cross-clade coverage under the tested conditions, and while the examples provide useful data for formulations, the Examples fail to provide predictable rules that extend across the full breath of the claimed genera. For instance, the specification does not provide working examples directed to any machine-learning identified H1 or B strain HAs, nor do any of the examples test any other SOCs from any other season or hemisphere. It is unclear as to the formulation of LNPs used to deliver the mRNAs in Example 2, and it is also unclear if any of the mRNA sequences were modified or had chemical modifications to the nucleotides (e.g. use of stabilizing agents in the mRNA, such as 5’/3’ UTRs, 5’ caps, 3’ poly A tails, or chemically modified nucleotides such as pseudouridine.) The disclosed examples therefore do not establish enablement across the full scope of the claims.
Guidance in the specification. The specification provides guidance regarding the delivery of inactivated influenza viruses comprising multiple H3 HAs or the delivery of quadrivalent or pentavalent HA-encoding mRNAs in LNPs. The specification also refers to the art as to different machine learning approaches. However, the specification does not provide sufficient guidance for identifying which additional HAs will satisfy the claim scope, what type of LNP formulation to use, how to chemically modify the mRNA, or what adjuvants may/may not assist in producing the functional outcomes. In particular, the specification does not explain which general structural feature is shared by qualifying machine-learning HAs, nor does it provide a validated selection threshold that distinguishes a successful additional antigen from an unsuccessful one. It does not provide sufficient guidance as to how to determine whether a selected HA will improve the breadth or strength of the immune response, or if it may result in interference with another component. The tested models in ferrets do not explain how one should extrapolate the results to other species, especially humans, especially in methods to reduce influenza symptoms or treat influenza disease.
Quantity of experimentation necessary. To practice the full scope of the claims, one skilled in the art would need to identify candidate HAs using one or more machine-learning approaches, select candidate sequences from SOCs, and determine whether each candidate remains a suitable influenza HA antigen and results in the functional outcomes claimed. The artisan would have to prepare the compositions in either format (protein or ribonucleic acid), combine said HAs in a composition, and tested against appropriate controls to determine efficacy, interference, enhancement, dosage, and other parameters. Such experimentation would not merely involve the routine application of known methods to embodiments reasonably expected to work. Instead, one skilled in the art would need to prepare and test additional embodiments to determine whether they satisfy the ability to generate an immunogenic composition, a vaccine composition, or the functional outcomes of dependent claims, as the specification itself has shown that antigen addition can produce different results depending on the selected strain, clade relationship, dose, and measured response. Although the individual methods used to prepare and test candidate embodiments may have been known in the art, the relevant inquiry is not whether one skilled in the art could perform the required assays. The relevant inquiry is whether the specification provides sufficient guidance to identify and practice the embodiments falling within the full scope of the claims without undue experimentation. Here, one skilled in the art would need to prepare and test additional HA sequences and multivalent formulations to determine which embodiments satisfy the claimed immunogenic and protective results.
Amgen. The Supreme Court has explained that a specification need not describe with particularity how to make and use every embodiment within a claimed class. However, the disclosure must enable one skilled in the art to make and use the full scope of the claimed invention. A reasonable amount of experimentation may be permissible depending on the nature of the invention and the underlying art. Amgen Inc. v. Sanofi, 598 U.S. 594, 610-13 (2023).
In the instantly claimed invention, the specification describes selected H3 combinations and a limited group of quadrivalent and pentavalent mRNA/LNP formulations evaluated in naïve ferrets, but the claims also encompass additional machine learning H1, B/Yamagata, and B/Victoria HA, additional wild-type and non-wild type sequences, multiple antigen formats, higher valency formulations beyond four or five HA, future SOC strains yet to be identified, and methods requiring protective results in any type of human subject. The specification does not identify a general quality or provide sufficient guidance that would allow one skilled in the art to practice that broader scope without undue experimentation.
Conclusion. For the reasons discussed above, the specification does not enable one skilled in the art to make and use the full scope of the invention recited in the instant claims without undue experimentation.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, 6-7, 9, 10, 16, 24-25, 32, 34, 36-37, 41-44, 52, 54, and 56-57 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ciaramella et. al. (US20180311336A1, Pub. 11/01/2018; CITED ART OF RECORD; hereafter “Ciaramella”.)
The Prior Art
Ciaramella teaches influenza virus ribonucleic acid (RNA) vaccines, namely mRNA vaccines, as well as methods of using the vaccines and compositions comprising the vaccines (entire document; see abstract; ¶[0012-0020].) Ciaramella teaches the vaccine would comprise at least one ribonucleic acid (RNA) polynucleotide having an open reading frame encoding at least one influenza virus antigenic polypeptide or an immunogenic fragment thereof, formulated in a lipid nanoparticle (LNP)(reference claim 1). Ciaramella teaches that the antigen may be HA (or fragments HA1 or HA2 or further fragments thereof; reference claim 2; ¶[0009][0014]), neuraminidase (NA), nucleoprotein (NP), matrix protein 1 (M1), matrix protein 2 (M2), non-structural protein 1 (NS1) and non-structural protein 2 (NS2)(reference claim 3). Ciaramella teaches the at least one antigenic polypeptide is from influenza virus strain H1/PuertoRico/8/1934 (H1N1), H1/New Caledonia/20/1999 (H1N1), H1/California/04/2009 (H1N1), H5/Vietnam/1194/2004, H2/Japan/305/1957, H9/Hong Kong/1073/99, H3/Aichi/2/1968 (H3N2), H3/Brisbane/10/2007 (H3N2), H7/Anhui/1/2013, H10/Jiangxi-Donghu/346/2013, H3/Wisconsin/67/2005 (H3N2), H1/Vietnam/850/2009 (H1N1), or a combination thereof (reference claim 6). Ciaramella teaches that the composition may comprise multiple influenza virus proteins (¶[0013]) of any one of or a combination of any or all of HA from H1, H2, H3, H4, H5, H6, H7, H8, H9, H10, H11, H12, H13, H14, H15, H16, H17, and/or H18)(¶[0015]). Ciaramella teaches that the composition may be multivalent (¶[0053]; reference claim 14), and may code at least five or at least ten antigenic polypeptides (¶[0044-0045]). Ciaramella teaches that the antigens would induce an immune response against seasonal or pandemic influenza strains (¶[0223]) and can be wild-type or non-wild-type sequences (¶[0027-0030]). Said non-wild-type sequences may be consensus HA antigens (¶[0113][0222][0582-0584]) wherein computer algorithms/programs can determine a consensus sequence from multiple HA alignments, such as H1N1 strains or H3 strains (¶[0583][0587-0588]; Table 5). Ciaramella therefore teaches every aspect of instant claims 1-4, 6-7, 9, 10, 16, 24-25, 32, 34, 36, 44, 52, and 54.
Ciaramella teaches further aspects of the instant claims. Ciaramella teaches HA antigens from influenza B strains, such as B/Yamagata and B/Victoria strains (Table 6; Fig. 16; ¶[0589-0593]; instant claims 56-57). Ciaramella teaches that animals previously vaccinated with inactivated influenza seasonal vaccines can be used to determine the efficacy of the antigens (¶[0596]; reference claim 26). Ciaramella teaches that adjuvants may be used in the compositions (¶[0025][0296][0328]; instant claim 37). Ciaramella teaches that at least one chemical modification to the mRNA may be present, such as the use of pseudouridine, to modify 5% up to 100% of the nucleotides (¶[0038][0284]; reference claim 60; instant claim 41), and that the vaccine is suitable for intramuscular injection (¶[0059][0080][0563]; instant claim 42). Ciaramella teaches that the LNP is comprised of a molar ratio of about 20-60% cationic lipid, 0.5-15% PEG-modified lipid, 25-55% sterol, and 25% non-cationic lipid (reference claim 54), wherein the sterol is a cholesterol, wherein the non-cationic lipid is a neutral lipid, which is DSPC or DOPE (reference claim 55; ¶[0345][0374][0496]; instant claim 43). Ciaramella teaches that the composition may be a single dose, or a prime/boost administration (¶[0056-0058[0116-0117]). Ciaramella teaches the mRNA may comprise additional stabilizing features, such as 5’/3’ UTRs, 5’ caps, 3’ polyA tails, and codon optimization (¶[0233][0285]). If additional influenza antigens are present, such as NA, sequences in Table 7 have been provided that teach such NA antigens from N1 and N2 subtypes.
Ciaramella therefore teaches every aspect of instant claims 1-4, 6-7, 9, 10, 16, 24-25, 32, 34, 36-37, 41-44, 52, 54, and 56-57, and anticipates the invention encompassed by said claims.
Claims 1-7, 9, 29-32, 34, 36-38, 41-44, 54, and 56-57 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Alefantis et. al. (US20230043128A1; Pub. 02/09/2023, Priority 06/18/2021; hereafter “Alefantis”) as evidenced by Naik et. al. (WO2021080999A1; Pub. 04/29/2021; CITED ART OF RECORD; hereafter “Naik”.)
The applied reference has a common inventor (Timothy Alefantis) with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
The Prior Art
Alefantis teaches octavalent influenza vaccine compositions comprising eight mRNA, each mRNA comprising an open reading frame encoding a different influenza antigen, wherein the compositions further comprise lipid nanoparticles (LNPs) for delivering said mRNA (entire document; see abstract.) Alefantis teaches that multiple influenza HA antigens would be in the composition, such as influenza A HA antigens from H1 and H3 subtypes and influenza B HA from B/Yamagata and B/Victoria lineages (reference claims 1-3). Alefantis teaches the influenza antigens comprise an influenza virus HA antigen and/or an influenza virus NA antigen having a molecular sequence identified or designed from a machine learning model (¶[0060][0163]; reference claim 51.) Alefantis therefore teaches the limitations of instant claims 1-4, 9, 32, 34, and 56-57.
Alefantis teaches that the machine learning model either identifies an HA protein or designs an HA protein, which implies the use of either wild-type or engineered HA sequences (¶[0163][0166-0167]; instant claims 5-7). Alefantis teaches that current influenza vaccines are live attenuated or inactivated (¶[003]). Alefantis teaches that the composition may comprise an H1 HA, an H3 HA, and that the machine learning HA further comprises one or more mRNA encoding H1 HA, H3 HA, B/Yamagata HA, or B/Victoria HA or any combination thereof (¶[0164-0166]), and that the HA antigens selected may be from different strains and elicit improved immune responses against one or more seasonal or pandemic influenza strains (¶[0161-0162][0240-0241]). Alefantis teaches the machine learning models can predict biological responses (¶[0167]; instant claim 29) and incorporates the teachings of Naik, which teach that the biological responses predicted may be from mice, ferrets, or humans (¶[0036] Naik; instant claim 30) and can test the biological responses with assays such as hemagglutination inhibition assay (HAI) and antibody forensics (AF)(¶[0050]; instant claim 31). Alefantis teaches the HA may be selected from H1N1 and/or H3N2 strains (¶[0010]; instant claim 36). Alefantis teaches the use of AF03, an squalene-based oil-in-water emulsion adjuvant (¶[0063][0290]; instant claims 37-38). Alefantis teaches the mRNA may have modified nucleotides, such as pseudouridines (¶[0168][0206-0207]; instant claim 41). Alefantis teaches the composition is formulated for intramuscular injection (¶[0049-0052]; instant claim 42). Alefantis teaches that the LNP can comprise a cationic lipid at a molar ratio of 40%; a PEGylated lipid at a molar ratio of 1.5%; a cholesterol-based lipid at a molar ratio of 28.5%; and a helper lipid at a molar ratio of 30% (¶[0021-0046]; reference claim 28; instant claim 43). Alefantis teaches a method of eliciting an immune response in a subject in need thereof, comprising administering to the subject, optionally intramuscularly, intranasally, intravenously, subcutaneously, or intradermally, a prophylactically effective amount of the influenza vaccine composition (¶[0051]; reference claim 42; instant claim 44). Alefantis teaches a method of reducing one or more symptoms of an influenza virus infection through administration of an effective amount of the vaccine composition (¶[0052]; reference claim 43; instant claim 54).
Alefantis, as evidenced by Naik, teaches every aspect of instant claims 1-7, 9, 29-32, 34, 36-38, 41-44, 54, and 56-57, and anticipates the invention encompassed by said claims.
Claims 1-7, 9, 29-32, 34, 36-38, 41-44, 54, and 56-57 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Casimiro et. al. (US20220142923A1; Pub. 05/12/2022, Priority 11/06/2020; hereafter “Casimiro”), or, in the alternative, one of the following family members (also authored by Casimiro et. al. ) with the same disclosure and priority date
US20220347100A1, Priority 11/16/2020;
US20220378701A1, Priority 11/16/2020;
US20240148651A1, Priority 11/16/2020;
US20240091154A1, Priority 11/16/2020;
US20260102349A1, Priority 11/16/2020; as evidenced by Naik et. al. (WO2021080999A1; Pub. 04/29/2021; CITED ART OF RECORD; hereafter “Naik”.)
The applied reference has a common assignee (Sanofi/Sanofi Pasteur) with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
NB: The rejection will use the ‘923 PGPub paragraph numbering for the rejection.
The Prior Art
Casimiro teaches lipid nanoparticles (LNPs) for delivering nucleic acids such as mRNA, as well as methods of making and using lipid nanoparticles for delivering nucleic acids such as mRNA (entire document; see abstract.) Casimiro teaches at least one of the one or more influenza virus proteins comprises an influenza virus HA protein and/or an influenza virus NA protein having a molecular sequence identified or designed from a machine learning model, and in certain embodiments, at least one of the one or more ribonucleic acid molecules encode one or more influenza virus proteins having a molecular sequence identified or designed from a machine learning model (¶[0124]). Casimiro teaches the composition comprises two, three, four, five, six, seven, eight, nine, or more mRNA molecules encoding (i) one or more HA antigens, (ii) one or more NA antigens, or (iii) a combination of one or more HA antigens and NA antigens (¶[0125]). Casimiro teaches the influenza antigens may be selected from a combination of one or more HA antigens and NA antigens, selected from H1N1, H3N2, H2N2, H5N1, H7N9, H7N7, H1N2, H9N2, H7N2, H7N3, H5N2, and H10N7 subtypes and/or B/Yamagata and B/Victoria lineages (¶[0126]), wherein the composition comprises at least one mRNA molecule encoding an H3 HA antigen, one mRNA molecule encoding an H1 HA antigen, one mRNA molecule encoding an HA antigen from the Influenza B/Yamagata lineage, and one mRNA molecule encoding an HA antigen from the Influenza B/Victoria lineage (¶[0127]). Casimiro teaches the composition would be a multivalent mRNA composition that is encapsulated within LNPs (¶[0121-0122]). Casimiro therefore teaches the limitations of instant claims 1-4, 9, 32, 34, and 56-57.
Casimiro teaches that the machine learning model either identifies an HA protein or designs an HA protein, which implies the use of either wild-type or engineered HA sequences (¶[0124][0129-0130]; instant claims 5-7). Casimiro teaches that current influenza vaccines are inactivated (¶[0384]). Casimiro teaches that the composition may comprise an H1 HA, an H3 HA, and that the machine learning HA further comprises one or more mRNA encoding H1 HA, H3 HA, B/Yamagata HA, or B/Victoria HA or any combination thereof (¶[0128-0130]), and that the HA antigens selected may be from different strains and elicit improved immune responses against one or more seasonal or pandemic influenza strains (¶[0228-0229]). Casimiro teaches the machine learning models can predict biological responses (¶[0130]; instant claim 29) and incorporates the teachings of Naik, which teach that the biological responses predicted may be from mice, ferrets, or humans (¶[0036] Naik; instant claim 30) and can test the biological responses with assays such as hemagglutination inhibition assay (HAI) and antibody forensics (AF)(¶[0050] Naik; instant claim 31). Casimiro teaches the HA may be selected from H1N1 and/or H3N2 strains (¶[0126]; reference claim 22; instant claim 36). Casimiro teaches the use of AF03, an squalene-based oil-in-water emulsion adjuvant (¶[0052][0258]; instant claims 37-38). Casimiro teaches the mRNA may have modified nucleotides, such as pseudouridines (¶[0131][0151-0152]; instant claim 41). Casimiro teaches the composition is formulated for intramuscular injection (¶[0030-0032][0162]; instant claim 42). Casimiro teaches that the LNP comprises a cationic lipid at a molar ratio between 35% and 45%, a polyethylene glycol (PEG) conjugated (PEGylated) lipid at a molar ratio between 0.25% and 2.75%, a cholesterol-based lipid at a molar ratio between 20% and 35%, and a helper lipid at a molar ratio of between 25% and 35%, wherein all the molar ratios are relative to the total lipid content of the LNP (¶[0004-0007]; reference claim 1; instant claim 43). Casimiro teaches a method of eliciting an immune response in a subject in need thereof, comprising administering to the subject, optionally intramuscularly, intranasally, intravenously, subcutaneously, or intradermally, a prophylactically effective amount of the influenza vaccine composition (¶[0032]; reference claim 48; instant claim 44). Casimiro teaches a method of reducing one or more symptoms of an influenza virus infection through administration of an effective amount of the vaccine composition (¶[0225][0230-0231]; reference claim 49; instant claim 54).
Casimiro, as evidenced by Naik, teaches every aspect of instant claims 1-7, 9, 29-32, 34, 36-38, 41-44, 54, and 56-57, and anticipates the invention encompassed by said claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 5, 8, 14, 20, 22, 26-31, 33, and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Ciaramella as applied to claims 1-4, 6-7, 9-10, 16, 24-25, 32, 34, 36-37, 41-44, 52, 54, and 56-57 above, and further in view of Cortes-Garcia et. al. (US20170121373A1; Pub. 05/04/2017; hereafter “Cortes-Garcia”);
Hayati et. al. (Hayati M, et. al. Proc Biol Sci. 2020 Apr 8;287(1924):20200319. Epub 2020 Apr 8.; hereafter “Hayati”); and
Bonomo et. al. (Bonomo ME, et. al. Clin Infect Dis. 2018 Sep 14;67(7):1129-1131.; hereafter “Bonomo”.)
Nabel et. al. (WO2019195284A1; Pub. 10/10/2019; hereafter “Nabel”.)
The Prior Art The teachings of Ciaramella have been set forth supra. While Ciaramella teaches that computer algorithms can be used to generate non-wild-type sequences, Ciaramella fails to teach other aspects of the computer programs, such as identification of wild-type sequences for inclusion in the influenza vaccine, the use of predictive biological outcomes, or the inclusion of similar or different variants/clades within the same influenza subtype. However, such limitations were known optimizations in the influenza vaccine art, as evidenced by Cortes-Garcia, Hayati, Bonomo, and Nabel.
Cortes-Garcia teaches compositions and methods for analyzing the expression and conformation of engineered influenza hemagglutinin (HA), and, in particular, provides methods of screening in silico designed HA antigens using neutralizing antibody panels specific to conserved epitopes. In some embodiments, the HAs are down selected for inclusion in universal influenza vaccines based upon their binding to neutralizing antibody panels in immunostaining assays (entire document; see abstract.) Cortes-Garcia teaches that the designed HA sequences can be screened in silico for preclinical or clinical studies (¶[0156]) and that the inventive assays provided by Cortes-Garcia not only identify and validate engineered HA antigens that are properly expressed and structurally sound, but also predict the breath and/or specificity of immunogenicity of engineered HA antigens (¶[0003]). Cortes-Garcia notes that the biological activity can be observed (¶[0060]) such as through neutralization assays or hemagglutinin inhibition assays (HAI), wherein a HAI with immune sera obtained from injected host animals may be used to measure neutralizing antibody responses (¶[0068][0150]; instant claim 31). The “host” as taught by Cortes-Garcia may be a human or non-human animal, such as a mouse or ferret (¶[0055][0081][0149]; instant claim 30). Cortes-Garcia notes their assays and methods may be used to predict, assess and/or validate specificity against strain clusters based on anti-head antibody binding analysis (¶[0041][0150][0171-0172]) through computer or other processing sources or algorithms (¶[0066][0106-0108]; instant claim 29).
Hayati teaches which natural variants are likely to circulate successfully (entire document; see abstract.) Hayati teaches testing H3N2 and H1N1 variants for the prediction of future expansion of subtrees of these viruses (entire document; see abstract) and notes machine learning models/algorithms that predict the use of current viral isolates or new emergent strains (Sect. 2 “Results”; instant claim 5).
Bonomo teaches prediction of vaccine efficacy with a measure of antigenic distance between influenza A(H3N2) and vaccine viruses based on amino acid substitutions in the dominant HA epitope (entire document; see abstract.) Bonomo teaches that increased antigenic distance between the vaccine and the infecting virus leads to decreased vaccine efficacy (p. 1129, left col., ¶1), and that several antigenically similar candidate viruses may be available and that it is critical to choose a vaccine strain having minimal antigenic distance from circulating strains (p. 1131; left col., ¶2). Bonomo teaches evaluation of A/Colorado/15/2014, a representative clade 3C.2a strain, and finds that the dominant epitope in this isolate is B, with amino acid substitutions T160K and L194P (Results, p. 1132). Bonomo also teaches that rather than an increased antigenic distance due to virus evolution, the 2016-2017 vaccine may have diverged from circulating viruses due to substitutions acquired during isolation of the CVV strains in eggs, and that passaging-related adaptations have posed an issue for A(H3N2) CVVs in particular with emergence of subclades 3C.3a and 3C.2a (p. 1129, rt. Col., ¶1).
Bonomo teaches that current vaccines include recombinant influenza antigens produced in insect cells from baculovirus expression systems (FLUBOK® is expressed from a modified baculovirus in insect cells, namely Spodoptera frugiperda cells) or inactivated influenza viruses such as FLUZONE® or FLUCELVAX® (“Discussion”, p. 1131), and since both systems are known HA antigen delivery systems, it would be obvious to a skilled artisan to deliver designed HA in either system, as such systems are generally acceptable worldwide as influenza vaccine delivery systems and would be an obvious modification for delivering the HA antigens selected if mRNA technology was unavailable (instant claims 8, 33, 35).
Nabel teaches multivalent influenza vaccine compositions (entire document; see Fig. 21, ¶[0056]) wherein it is sometimes useful to utilize multiple subtype antigens from divergent viruses (Sect. 4, ¶[0262-0273]) or use multiple antigens from the same virus, such as both HA and NA (¶[00199]). Nabel teaches the compositions are useful to elicit an immune response or protect against influenza virus infection (¶[0075][0197-0198][0213]), and that the inclusion of additional HA antigens, even from the same subtype, was useful for increasing the range of protective antibody responses (¶[0055][0272]). Nabel teaches the antigens may be computationally optimized broadly reactive antigens (COBRA)(¶[0053]). Nabel teaches the compositions may comprise ADDAVAX™, MF59, and AS03 adjuvants, which are all squalene-in-water adjuvants (¶[00208]; instant claim 38).
Given the teachings of Ciaramella, a skilled artisan would find it obvious to deliver multiple HA antigens in a single multivalent composition. Such a method was supported by further prior art using different multivalent delivery modalities of said HA, as evidenced by Nabel, Hayati, Cortes-Garcia, and Bonomo. Given the teachings of Cortes-Garcia, Hayati, and Bonomo, different computer algorithms, programs, or processing models were known and available to aid in the prediction of clinically relevant HA strains/subtypes, whether said strains/subtypes were antigenically similar or dissimilar, and the predicted biological outcome in the use of said strains/subtypes. Given the suggestion by these models, it might be useful to include or exclude certain HA sequences, wherein inclusion of different subtypes, regardless of antigenic similarity or dissimilarity, would potentially aid in allowing more H1, H3, B/Yamagata, or B/Victoria HA to be recognized by the host, as suggested by Nabel and noted by Bonomo, which highlighted that vaccines would be more efficacious the closer they were antigenically to the dominant epitope, so inclusion of multiple HA from the same or different subtypes/clades may be warranted depending on the evolution from the dominant epitope. Taken as a whole, the combined teachings of Ciaramella, Nabel, Hayati, Cortes-Garcia, and Bonomo, it would be obvious to include multiple HA antigens in a singular influenza composition, it would be obvious to use both naturally-occurring and computationally designed/engineered HA sequences in order to effectuate the most clinically relevant immune response, and there are a number of known and used vaccine modalities for delivering such HA in the art. Given the circulating strains at the time, the art suggested that it might be warranted to include HA which were from the same or different subtypes/clades. Arriving at the different limitations of instant claims 5, 8, 14, 20, 22, 26-31, 33, and 35 would be obvious to a skilled artisan, given what was known in the art at the time of filing.
It would have been obvious to one of ordinary skill in the art to modify the methods and compositions taught by Ciaramella in order to use computer models or algorithms to further predict what HA subtypes/variants/isolates/clades should or should not be included in the immunogenic composition and to use said models to predict the biological response to said HA in the target host. One would have been motivated to do so, given the suggestion by Hayati, Cortes-Garcia, and Bonomo that these algorithms, models, and computer programs were used in the art to attempt to predict which circulating variants could/should or could/should not be used together in order to elicit the most appropriate response to circulating influenza variants without causing interference. There was sufficient motivation in the art to include multiple antigens from the same or different subtype and/or clade, as taught by Nabel, in order to effectuate the most clinically relevant response to the viruses circulating at that time. Thus, the invention as a whole was clearly prima facie obvious to one of ordinary skill in the art at the time the invention was made.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-7, 9-10, 14, 16, 20, 22, 24-32, 34-38, 41-44, 52, 54, and 56-57 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-34 of U.S. Patent No. 11,771,652 in view of Ciaramella (supra) and Dong et. al. (US20130158021A1; Pub. 06/20/2013; hereafter “Dong”).
Both sets of claims are drawn to compositions comprising multivalent mRNA encoding multiple influenza HA antigens within LNPs. Said HA can be from H1, H3, or influenza B HA (B/Yamagata and B/Victoria). Both claim at least one HA antigen within the composition is present from a machine learning model. Both claim chemical modifications of the mRNA and intramuscular administration of the composition. The main difference is that the ‘652 claims are drawn to the additional presence of other antigens, such as influenza NA antigens, and provides further details on the LNP compositions, stabilizers in the composition, and mRNA structural features. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, NA N1 and N2 sequences which may be included, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). Additionally, Ciaramella teaches the stabilizing features one can make to mRNA, such as codon optimization, 5’ caps, 3’ polyA tails, 5’/3’UTRs, and chemical modifications to the nucleotides, such as through the use of pseudouridine. While Ciaramella teaches different cationic lipids within the LNPs, Dong teaches other cationic lipids useful in LNPs for delivery of RNA, such as ckk-e10 (Tables 4-5; ¶[0587]). For at least these reasons, the instant claims and the ‘652 claims are not patentably distinct, especially in light of the teachings of Ciaramella and Dong.
Claims 1-7, 9-10, 14, 16, 20, 22, 24-32, 34-38, 41-44, 52, 54, and 56-57 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-9, 11-27, 33-41, and 46-53 of U.S. Patent No. 11,771,653 in view of Ciaramella (supra) and Casimiro et. al. (US20220142923A1; Pub. 05/12/2022, Priority 11/06/2020; hereafter “Casimiro”).
The applied reference (Casimiro) appears to have a common assignee with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
Both sets of claims are drawn to compositions comprising multivalent mRNA encoding multiple influenza HA antigens within LNPs. Said HA can be from H1, H3, or influenza B HA (B/Yamagata and B/Victoria). Both claim at least one HA antigen within the composition is present from a machine learning model. Both claim chemical modifications of the mRNA and intramuscular administration of the composition. The main difference is that the ‘653 claims are drawn to the additional presence of other antigens, such as influenza NA antigens, and provides further details on the LNP compositions, stabilizers in the composition, and mRNA structural features. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, NA N1 and N2 sequences which may be included, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). Additionally, Ciaramella teaches the stabilizing features one can make to mRNA, such as codon optimization, 5’ caps, 3’ polyA tails, 5’/3’UTRs, and chemical modifications to the nucleotides, such as through the use of pseudouridine. While Ciaramella teaches different cationic lipids within the LNPs, Casimiro teaches other cationic lipids useful in LNPs for delivery of RNA, such as GL-HEPES-E3-E12-DS-4-E10 (reference claims 1-3). For at least these reasons, the instant claims and the ‘653 claims are not patentably distinct, especially in light of the teachings of Ciaramella and Casimiro.
Claims 1-7, 9-10, 14, 16, 20, 22, 24-32, 34-38, 41-44, 52, 54, and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 7, 12, 16, 18-19, 21-22, 31, 42, 48-49, and 55-56 of copending Application No. 19/330,237 in view of Ciaramella (supra) and Karve et. al. (US20190298755A1; Pub. 10/03/2019; hereafter “Karve”). Both sets of claims are drawn to compositions comprising multivalent mRNA encoding multiple influenza HA antigens within LNPs. Said HA can be from H1, H3, or influenza B HA (B/Yamagata and B/Victoria). Both claim at least one HA antigen within the composition is present from a machine learning model. Both claim chemical modifications of the mRNA and intramuscular administration of the composition. Both claim methods of eliciting therapeutic immune responses through administration of these compositions, or methods of preventing influenza symptoms. The main difference is that the ‘237 claims are drawn to the additional presence of influenza NA antigens, and provides further details on the LNP composition and mRNA structures. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, NA N1 and N2 sequences which may be included, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). While Ciaramella teaches different cationic lipids within the LNPs, Karve teaches other cationic lipids useful in LNPs for delivery of mRNA, such as OF-02 (¶[0013][0176][0219]). For at least these reasons, the instant claims and the ‘237 claims are not patentably distinct, especially in light of the teachings of Ciaramella and Karve.
This is a provisional nonstatutory double patenting rejection.
Claims 1-7, 9-10, 14, 16, 20, 22, 24-32, 34-38, 41-44, 52, 54, and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-4, 8, 12-13, 19, 27-28, 32-33, 35-36, 38-40, 42-43, 45, and 52-75 of copending Application No. 17/843,445 in view of Ciaramella (supra) and Karve et. al. (US20190298755A1; Pub. 10/03/2019; hereafter “Karve”). Both sets of claims are drawn to compositions comprising multiple influenza HA antigens, wherein an HA antigen must be from H1, H3, B/Yamagata, and B/Victoria, and can include additional HA antigens. Both claim the HA is encoded by mRNA and that said mRNA may be formulated in a LNP. Both claim the same compositions of general lipids within the LNP of helper lipids, cationic lipids, PEGylated lipids, and cholesterol-based lipids. Both claim the formula is suitable for intramuscular injection, and both claim the use of modified nucleotides in the mRNA. Both claim methods of eliciting therapeutic immune responses through administration of these compositions, or methods of preventing influenza symptoms. The main difference is that the ‘445 claims are drawn to the additional presence of influenza NA antigens, and provides further details on the LNP composition and mRNA structures, while the instant claims provide for additional HA in the composition that was identified via a machine learning model. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, NA N1 and N2 sequences which may be included, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). While Ciaramella teaches different cationic lipids within the LNPs, Karve teaches other cationic lipids useful in LNPs for delivery of mRNA, such as OF-02 (¶[0013][0176][0219]). For at least these reasons, the instant claims and the ‘445 claims are not patentably distinct, especially in light of the teachings of Ciaramella and Karve.
This is a provisional nonstatutory double patenting rejection.
Claims 1-7, 9-10, 14, 16, 20, 22, 24-32, 34-38, 41-44, 52, 54, and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 7-12, 15-17 of copending Application No. 18/653,422 in view of Hayati, Nabel, and Bonomo (all detailed supra).
Both sets of claims are drawn to compositions comprising multiple influenza HA antigens, wherein an HA antigen must be from H1, H3, B/Yamagata, and B/Victoria, and can include additional HA antigens. Both claim the use of squalene-in-water adjuvants or liposome-based adjuvants. Both claim the formula is suitable for intramuscular injection. Both claim methods of eliciting therapeutic immune responses through administration of these compositions, or methods of preventing influenza symptoms. The main difference is that the ‘422 claims are drawn to the additional presence of influenza NA antigens, while the instant claims provide for additional HA in the composition that was identified via a machine learning model. However, these differences would be obvious, given the teachings of Hayati, Nabel, and Bonomo (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, NA sequences which may be included, how to computationally determine which antigens should be included, and learning models that can predict the most useful antigens and the potential response in the host (see 103 rejection supra). For at least these reasons, the instant claims and the ‘422 claims are not patentably distinct, especially in light of the teachings of Hayati, Nabel, and Bonomo.
This is a provisional nonstatutory double patenting rejection.
Claims 1-10, 14, 16, 20, 22, 24-38, 41-44, 52, 54, and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-4, 6-7, 12-13, 15-18, 20, 25-29, 32, 34, 37, 48-52, and 60-61 of copending Application No. 18/653,458 in view of Ciaramella (detailed supra).
Both sets of claims are drawn to compositions comprising multiple influenza HA antigens in different forms (protein or nucleic acid), wherein an HA antigen must be from H1, H3, B/Yamagata, and B/Victoria, and can include additional HA antigens. Both claim the antigens may be mRNA, recombinant proteins, or in inactivated influenza virus particles. Both claim the use of machine learning models to select the sequences. Both claim the use of squalene-in-water adjuvants or liposome-based adjuvants. Both claim the formula is suitable for intramuscular injection. Both claim the use of chemically modified nucleotides, and that the ribonucleic acid molecules may be encapsulated within an LNP, wherein both claim the same compositions of LNPs. Both claim methods of eliciting therapeutic immune responses through administration of these compositions, or methods of preventing influenza symptoms.
The main difference is that the ‘458 claims are drawn to the additional presence of influenza NA antigens. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, NA N1 and N2 sequences which may be included, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). For at least these reasons, the instant claims and the ‘458 claims are not patentably distinct, especially in light of the teachings of Ciaramella.
This is a provisional nonstatutory double patenting rejection.
Claims 1-10, 14, 16, 20, 22, 24-38, 41-44, 52, 54, and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-12 and 14-19 of copending Application No. 19/410,181 in view of Ciaramella (supra) and Karve et. al. (US20190298755A1; Pub. 10/03/2019; hereafter “Karve”).
Both sets of claims are drawn to compositions comprising multiple influenza HA antigens, wherein an HA antigen must be from H1, H3, B/Yamagata, and B/Victoria, and can include additional HA antigens. Both claim the HA is encoded by mRNA and that said mRNA may be formulated in a LNP. Both claim the same compositions of general lipids within the LNP of helper lipids, cationic lipids, PEGylated lipids, and cholesterol-based lipids. Both claim methods of eliciting therapeutic immune responses through administration of these compositions, or methods of preventing influenza symptoms. The main difference is that the ‘181 claims provide further details on the LNP composition and mRNA structures, while the instant claims provide for additional HA in the composition that was identified via a machine learning model. However, these differences would be obvious, given the teachings of Ciaramella (detailed supra) which describe the use of consensus sequence HA, multivalent HA compositions that include further influenza antigens, LNP composition, the identity of different lipids within LNPs and the % composition of said lipids, and administration schedules of the compositions (see 102 rejection supra). While Ciaramella teaches different cationic lipids within the LNPs, Karve teaches other cationic lipids useful in LNPs for delivery of mRNA, such as OF-02 (¶[0013][0176][0219]). For at least these reasons, the instant claims and the ‘181 claims are not patentably distinct, especially in light of the teachings of Ciaramella and Karve.
This is a provisional nonstatutory double patenting rejection.
Conclusion
No claims are allowed.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is listed below.
US20240252612A1. Teaches multivalent mRNA/LNP encoding both influenza HA and RSV F protein. Relevant to the state of the art; post-filing art.
WO2023196914A1. Teaches multivalent mRNA/LNP encoding at least eight influenza HA. Relevant to the state of the art; post-filing art.
US20260007735A1. Teaches mRNA/LNP encoding influenza antigens such as M1, NA, and HA to form VLPs. Relevant to the state of the art; post-filing art.
Sequeira DP, et. al. Vaccine. 2018 May 24;36(22):3112-3123. Epub 2017 Mar 11. Teaches VLPs from multiple H3 HAs produced in baculovirus/insect cell production system. Not utilized as rejection would be redundant to those set forth supra.
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/RACHEL B GILL/
Primary Examiner, Art Unit 1671
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