DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The IDS filed 9/13/2022 has been considered by the Examiner.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Priority of US application 63/025135 filed 5/14/2020 is acknowledged.
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 1-34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-30 are drawn to a method, so a process.
Claims 31-32 are drawn to non-transitory computer readable media, so a manufacture.
Claims 33-34 are drawn to a computer system comprising a process, so a machine.
Step 2A Prong One: Identification of an Abstract Idea
The claim(s) recite(s):
1. Accessing a molecule database and obtaining a target molecule.
This step reads on a mental process of considering a table or list of target molecules. The step is therefore an abstract idea.
2. Slicing the target molecule into molecular fragments.
This step reads on a process of separating the molecular components of a molecule which can be performed by the human mind and is therefore an abstract idea.
3. Determining a fragment frequency of a plurality of molecular fragments of the target molecule.
The instant step reads on a decision making process that can be performed by the human mind and is therefore an abstract idea.
4. Calculating molecular descriptors for the molecular fragments.
The instant step reads on a mental process of calculating or math and is therefore an abstract idea.
5. Calculating a synthetic difficulty score for the target molecule
The instant step reads on a mental process of calculating or math and is therefore an abstract idea.
Claim 15 is drawn to:
1. Selecting a target molecule.
The instant step reads on a mental process of selecting and is therefore an abstract idea.
2. Decomposing the target molecule into molecular fragments.
This step reads on a process of separating the molecular components of a molecule which can be performed by the human mind and is therefore an abstract idea.
3. Calculating a synthetic difficulty score for the molecular fragments for the target molecule.
The instant step reads on a mental process of calculating or math and is therefore an abstract idea.
4. Determining a sum of synthetic difficulty scores for the molecular fragments.
The instant step reads on a mental process of summing numerical values or math and is therefore an abstract idea
5. Determining a fragment density of the molecular fragments.
The instant step reads on a mental analysis or mathematics of calculating density and is therefore an abstract idea.
6. Calculating the synthetic accessibility score from the sum of synthetic difficulty scores and fragment densities.
The instant step reads on a mental process of calculating or math and is therefore an abstract idea.
7. Proving the synthetic accessibility score for the target molecule.
The instant step reads on a mental process of thinking to determine a score and is therefore an abstract idea
Claims 2-14 and 16-30 further recite steps that read on mental processes and math and are therefore also abstract ideas.
Step 2A Prong Two: Consideration of Practical Application
The claimed process results in a step of calculating and storing a difficulty score (claim 1) and calculating and providing a synthetic accessibility score (claim 15), which are abstract idea steps with extra solution activity of storing or outputting. See MPEP 2106.05(g). The claims do not recite any additional elements that integrate the abstract idea into a practical application.
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than
a drafting effort designed to monopolize the exception.
Step 2B: Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea. The recited additional elements are drawn to:
1. Storing the synthetic difficulty score in a database having a plurality of synthetic difficulty scores for a plurality of molecules, as in claim 1.
2. providing the synthetic accessibility score, as in claim 15.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because storing a determined result and providing a numerical value which reads on outputting are both tangential extra solution activities as described in MPEP 2106.05(g). The steps are well known, routine and conventional limitations that do not add significantly more to the recited abstract idea.
Other elements of the method include non-transitory computer readable medium (claims 31-32) and a processor (claims 33-34) which is a recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112-2nd 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 18-19 and 29 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 pre-AIA the applicant regards as the invention.
Claim 18 recites calculating molecular properties for fragments whose properties cannot be obtained from the trained model. This limitation is indefinite because the claims do not recite what the trained model is or its structure or other parameters one would use to determine if properties cannot be obtained from the trained model. It is unclear how one would determine if properties “cannot be obtained from the trained model” and what the metes and bounds of the conditions are such that properties “cannot be obtained from the trained model.”
Claim 19 recites calculating fragment density functions from fragments whole fragment density functions cannot be obtained from the trained model. This limitation is indefinite because the claims do not recite what the trained model is or its structure or other parameters one would use to determine if density functions from fragments cannot be obtained from the trained model. It is unclear how one would determine if density functions from fragments “cannot be obtained from the trained model” and what the metes and bounds of the conditions are such that fragments “cannot be obtained from the trained model.”
Claim 29 recites “a vendor” database is not “present.” The metes and bounds of a “vendor” database is unclear as well as well as what is meant by not being “present.” It is not clear where the presence of the vendor is intended so as to determine when it is not present.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims under 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of 35 U.S.C. 103(c) and potential 35 U.S.C. 102(e), (f) or (g) prior art under 35 U.S.C. 103(a).
Claims 1-34 are rejected under 35 U.S.C. 103(a) as being unpatentable over Ertl et al. (Journal of Cheminformatics, vol. 1 (2009) pgs 1-11; 8/13/2022).
Ertl et al. teach (Abstract) accessing PubChem a database of one million representative molecules; target structures may be computed (page 2, col. 1, par. 2)(i.e. accessing a molecule database and obtaining a target molecule; selecting a target molecule), as in claims 1 and 15.
Ertl et al. teach (page 3, col. 2, par. 2) calculating a fragment score which is a sum of contributions of all fragments in the molecule divided by the number of fragments in this molecule; Ertl et al. teach fragmenting molecules (page 3, col. 2, par. 3)(i.e. slicing the target molecule into molecular fragments; decomposing the target molecule into fragments), as in claims 1 and 15.
Ertl et al. teach (page 3, col. 2, par. 3) determining a frequency of occurrence of fragments (i.e. determining a fragment frequency of a plurality of molecular fragments of the target molecule; determining a fragment density of fragments), as in claims 1 and 15.
Ertl et al. teach determining structural features including ringComplexityScore, stereoComplexityScore, macrocyclePentalty and sizePenalty (page 4, col. 1-2) wherein the scores characterize sections of the molecule (i.e. calculating molecular descriptors for the molecular fragments; calculating a synthetic difficulty score for fragments), as in claims 1 and 15.
Ertl et al. teach that the synthetic accessibility is based on a “fragmentScore” (page 3, col. 2, par. 2) calculated as a sum of contributions of all fragments in the molecule divided by the number of fragments in this molecule (i.e. determining a sum of synthetic difficulty scores for the fragments), as in claim 15.
Ertl et al. teach (page 3, col. 2, par. 2) that sum of contributions of all fragments in the molecule divided by the number of fragments in this molecule; Ertl et al. also teach (page 4, col. 1, par. 1) a “complexityScore” as a number that characterizes
the presence of complex structural features in the molecules (i.e. determining a fragment density of the molecular fragments), as in claim 15.
Ertl et al. teach (page 3, col. 2, par. 2) synthetic accessibility as the combination of fragment score and “complexityPenelty” (i.e. calculating a synthetic difficulty score; calculating the synthetic accessibility score from the sum of synthetic difficulty score and fragment densities), as in claims 1 and 15.
Ertl et al. do not specifically teach storing the synthetic difficulty score in a database having a plurality of synthetic difficulty scores for a plurality of molecules, as in claim 1. Ertl et al. do not specifically teach “providing” the synthetic accessibility score for the target molecule, as in claim 15.
However, Ertl et al. teach (page 6, col. 1, par. 1) making the SAscore program as broadly available as possible and validating the synthetic accessibility score for 40 molecules (page 6, col. 2) which suggests that the scores were stored and retrieved in order to perform the validation. Ertl et al. also teach various data bases for accessing and storing cheminformatic data (page 6, col. 1-2). It would therefore be obvious to one of ordinary skill to store SAscores for computed target molecules for access. Ertl et al. provide motivation by teaching the need to make SAscore use broadly available. One of ordinary will would be successful in storing and providing target molecule synthetic accessibility through cheminformatic databases because synthetic accessibility is numerical information that can be effectively stored with other data charactering chemical molecules.
Regarding dependent claims 2-14 and 16-34
Ertl et al. teach fragment types fragmented from PubChem structures, as in claim 2 and 16.
Ertl et al. teach Asprim and fragments thereof (Figure 1) wherein substructures are obtained by fragmentation (i.e. valid druglike molecular structures and is invertible so that fragments can be converted into a target molecule), as in claim 3.
Ertl et al. teach a retrosynthetic tree leading to the molecules (i.e. retrosynthetic related decomposing function), as in claim 4.
Ertl et al. teach (Abstract, par. 2) that the molecular complexity score takes into account the presence of structural features such as rings, ring fusions, stereocomplexity and molecule size (i.e. evaluating chemical properties of synthesizable fragments and aggregating molecular descriptors), as in claims 5-6.
Regarding claims 7 and 24, Ertl et al. teach determining complexity scores for various molecular substructures (i.e. molecular descriptors) including for rings, stereo-structures and macrocycles (page 4, col. 1-2, connecting par.) and spiro rings and ring fusions. Ertl et al. also teach the molecular structures of the fragments (Figure 1) and therefore make obvious determining chiral carbon counts, ring counts, ring side chains counts, spiro count, biggest ring size, fused ring counts and bridge atoms all of which would be found in the molecular descriptor structures and substructures of the molecular fragments.
Ertl et al. teach the logarithm of the frequency versus fragment number to determine the frequency distribution of fragments (Figure 3) which also reads on a fragment density function, a in claims 8-9 and 25.
Ertl et al. teach (page 4, col. 1, par. 1) that their approach is based on assumption that the fragment frequency is related to their synthetic accessibility; substructures which are easy to prepare are present in molecules quite often, those which are difficult to synthesize or are unstable are rare (i.e. aggregating fragment information into fragment scores by taking fragment frequency into account), as in claims 10 and 26.
Ertl et al. teach a fragment frequency distribution (i.e. mathematical function) which calculates the contribution for each fragment as a ratio between the actual fragment count and the number of fragments forming 80% of all fragments in
the database. As a result the frequent fragments have positive scores and less frequent fragments have negative scores, as in claim 11 and 27.
Ertl et al. teach (page 4, col. 1, par. 1) that the fragment frequency is related to their synthetic accessibility which suggests a database of fragment scores, as in claim 12.
Ertl et al. teach (page 3, col. 2, par. 2) synthetic accessibility as the combination of fragment score and “complexityPenelty”, as in claim 13.
Ertl et al. teach (page 5, col. 1, par. 1) making the SAscore as broadly available as possible (i.e. providing the synthetic accessibility score), as in claim 14.
Ertl et al. teach (page 4, col. 1-2) ringComplexityScore, stereoComplexityScore, macrocyclePenalty and the sizePenalty (i.e. obtaining scores of fragments from a trained model), as in claims 17.
Ertl et al. teach (Figure 1) calculating properties of fragments by depicting their structures, as in claims 18 and 22-23.
Ertl et al. teach (Figure 3) a frequency distribution of fragments which reads on a fragment density function, as in claims 19 and 25.
Ertl et al. teach (page 6, col. 1, par. 1) processing large data sets with the SAscore (i.e. aggregating processed information to the synthetic accessibility score), as in claim 20.
Ertl et al. teach (page 2, col. 1, par. 2) retrosynthetic methods which build trees and rely on reaction databases where in one of ordinary skill would use retrosynthesis to determine molecular fragments based on knowledge of how the target molecule reacts, as in claim 21.
Ertl et al. teach a table of fragments (Figure 1) which is not a vendor of a synthesizable fragment, as in claim 29.
Ertl et al. teach (page 5, col. 1) that the synthetic accessibility score is scaled between 1 and 10, as in claim 28.
Ertl et al. teach (page 5, col. 2, par. 2) calculating the synthetic accessibility score for molecules from various databases wherein one of ordinary skill would know how to check, compare and add the scores to a database or array, as in claim 30.
Ertl et al. teach (page 6, col. 1, par. 1) the use of programming software suggesting a computer and therefore make obvious computer readable media and processors, as in claims 31-34.
E-mail communication Authorization
Per updated USPTO Internet usage policies, Applicant and/or applicant’s representative is encouraged to authorize the USPTO examiner to discuss any subject matter concerning the above application via Internet e-mail communications. See MPEP 502.03. To approve such communications, Applicant must provide written authorization for e-mail communication by submitting the following statement via EFS Web (using PTO/SB/439) or Central Fax (571-273-8300):
Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.
Written authorizations submitted to the Examiner via e-mail are NOT proper. Written authorizations must be submitted via EFS-Web (using PTO/SB/439) or Central Fax (571-273-8300). A paper copy of e-mail correspondence will be placed in the patent application when appropriate. E-mails from the USPTO are for the sole use of the intended recipient, and may contain information subject to the confidentiality requirement set forth in 35 USC § 122. See also MPEP 502.03.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Anna Skibinsky whose telephone number is (571) 272-4373. The examiner can normally be reached on 12 pm - 8:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Ram Shukla can be reached on (571) 272-7035. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Anna Skibinsky/
Primary Examiner, AU 1635