!201411124  In-silico drug design - all results obviously non-patentable?

But first, nothing to do with patents, but some interesting medical research, could it be that living at high altitudes makes you more depressed (less oxygen leads to less "happy" serotonin in the brain)? Article at: http://mic.com/articles/104096/there-s-a-suicide-epidemic-in-utah-and-one-neuroscientist-thinks-he-knows-why. One solution? Maybe a bit of coca tea, because the coca tea drinking/chewing people of La Paz, Bolivia, are quite happy, and live twice as high as people in Utah and Colorado. Or maybe it is their llama fetuses (you were about to ask, so check it out: http://www.lapazlife.com/places/the-witches-market-la-paz/).

Was I speaking of llama fetuses? Anyway, Senator Ted Cruz says Republicans should block all of Obama's presidential nominees for the next two years, I think in part because Obama wants to give U.S. citizenship to llama fetuses. In the LF-logic of Washington, this could happen, meaning Michelle Lee will not be officially made Director of the PTO. Which leads to a verifiable experiment. If officially appointed PTO Directors failed at improving patent pendency and quality and policy coherence, will/can an un-officially appointed PTO Director do any better/worse? If not, let's do something useful under 101, and get rid of the position, along with the very useful thing of getting rid of 101 itself. Ted Cruz article at: http://www.foxnews.com/politics/2014/11/23/cruz-calls-on-congress-to-block-presidential-nominees-over-executive-action/.

One last neat thing: the Melbourne Museum has produced a cool, 8 minute video of what it was like to be in Pompeii on 24 August 79 ACE, when the volcano exploded and destroyed the city. Video at: https://www.youtube.com/embed/dY_3ggKg0Bc.

---    In-silico drug design - all results obviously non-patentable?

      Next week, I will be on a panel at a biotech conference in Raleigh, North Carolina (www.insiliconf.org), on which I will be speaking about the patentability and patent insurance aspects of in silico drug design. In this PATNEWS, I explore these issues, and appreciate receiving any viewpoints on this topic, to add to my talk.

When you read the following, think to yourself, is the following scenario POSSIBLE, not rational/logical/scientific/meaningful: "Free Drugs v. Drug Designers of America, Justice Thomas writing for the court - 'It is obvious for drug designers to use drug design tools to design drugs - that's what's expected of PHOSITAs. Thus their results are too obvious to be patentable, and as they are the substance of the mathematical algorithms that represent the drugs inside the tools, they are prior art to themselves (c.f. Flook).'" Again, is this POSSIBLE, not rational/logical/scientific/meaningful? If so, I have an insurance policy for you.

And keep in mind that if you are filing patent applications today, you have to plan now for the next 20 years of even more advanced drug discovery tool development in parallel with the next 20 years of more judicial meltdown in logical thinking re 101.

      What is in-silico drug design? A review article appeared in the Brit.J. Pharmacology some years ago, "In silico pharmacology for drug discovery: methods for virtual ligand screening and profile" (Br. J. Pharm., Sept. 2007, 9-20, full text available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1978274/). I quote from the abstract:

Increasingly over the last decade however we have seen that computational (in silico) methods have been developed and applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, pharmacophores, homology models and other molecular modeling approaches, machine learning, data mining, network analysis tools and data analysis tools that use a computer. In silico methods are primarily used alongside the generation of in vitro data both to create the model and to test it. Such models have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization.

      And here is the issue - discovery and optimization - when done by the (undefinable) PHOSITA, will such novel molecules come close enough to the final invention that they are unpatentable under 35 USC 103? That is, is it obvious for one-skilled-in-the-art to use these automated drug discovery tools to create mostly-optimized novel molecules (with the final optimization being the typical lab testing, animal testing, human testing and FDA approval processes - all insignificantly innovative POST-SOLUTION ACTIVITIES)? I am not asking you this question from the point of view of rationality, but rather from the point of view for judicial (non)-thinking.

      The Swiss Institute of Bioinformatics has a nice diagram of information flows through multiple in-silico drug design tools (along with a list of multiple computer programs and databases). The diagram is available at: http://www.click2drug.org. The question is, how much user input is needed - how much real thinking does the PHOSITA do at the front end?

      For example, consider the following paper: "Development of a novel class of B-Raf(V600E)-selective inhibitors through virtual screening and hierarchical hit optimization", seeking chemicals to kill cancer cells. Article at: http://pubs.rsc.org/en/content/articlelanding/2012/ob/c2ob26081f#!divAbstract. Consider the abstract:

Oncogenic mutations in critical nodes of cellular signaling pathways have been associated with tumorigenesis and progression. The B-Raf protein kinase, a key hub in the canonical MAPK signaling cascade, is mutated in a broad range of human cancers and especially in malignant melanoma. The most prevalent B-RafV600E mutant exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, we describe the development of novel B-RafV600E selective inhibitors via multi-step virtual screening and hierarchical hit optimization. Nine hit compounds with low micromolar IC50 values were identified as B-RafV600E inhibitors through virtual screening.

Subsequent scaffold-based analogue searching and medicinal chemistry efforts significantly improved both the inhibitor potency and oncogene selectivity. In particular, compounds 22f and 22q possess nanomolar IC50 values with selectivity for B-RafV600Ein vitro and exclusive cytotoxicity against B-RafV600E harboring cancer cells.

      "development ... via multi-step virtual screening", "subsequent ... analog searching and medicinal chemistry". Is there any invention in a PHOSITA setting up a such a suite of drug discovery tools, and then doing standard chemistry to identify the best? Are these discoveries obvious? Will a standard question in infringement discovery now be "did you use drug discovery tools?"? Here's a more recent paper that first argues the the difficulty of drug discovery, even with some tools in the hands of a PHOSITA, and then shows how to make it easier. So is it becoming easily-enough to be obvious - again, not to be answered rationally, but Justice Thomas-y?

Cancer in silico Drug Discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.
FA San Lucas et al., Mol. Canc. Ther., Oct 2014

Abstract: Large-scale cancer data sets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: 1) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures, 2) finding candidate drugs to repress these expression signatures, and 3) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA.

      So mostly with automation, I can get to the point of in vitro testing of candidate drugs with cell lines to test them on. Since in vitro testing is INSIGNIFICANT POST-SOLUTION ACTIVITY (in vitro testing flunks every g*d-d**n piece of idiotic 101 case-law since Bilski/Mayo/Alice), all that is left, using the in-silico tools, is predictable experimentation done by a PHOSITA - which under KSR probably is too obvious to be patentable - to Justice Thomas.

      So we have to ask, as the in-silico tools become more powerful, will they reach a point of utility in the hands of a PHOSITA -- so that we can then use Alice+KSR to invalidate any patents on any drugs so discovered? Now, frankly, I would hope not. But the patent bar is allowing the Supreme Court and CAFC to get complete out of control with nonsense decisions that lead to possibilities such as the courts viewing drug discovery tools as "higher levels of achievement" that immediately trigger KSR for 103 attacks.

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      To put this into context (okay, you can't put something in context, when the context is idiotic ravings of scientifically ignorant judges, but we have no choice), let's turn to KSR:

The principles underlying these cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, Section 103 likely bars its patentability. For the same reason, if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill. Sakraida and Anderson’s-Black Rock are illustrative — a court must ask whether the improvement is more than the predictable use of prior art elements according to their established functions.


We build and create by bringing to the tangible and palpable reality around us new works based on instinct, simple logic, ordinary inferences, extraordinary ideas, and sometimes even genius. These advances, once part of our shared knowledge, define a new threshold from which innovation starts once more. And as progress beginning from higher levels of achievement is expected in the normal course, the results of ordinary innovation are not the subject of exclusive rights under the patent laws. Were it otherwise patents might stifle, rather than promote, the progress of useful arts.

      In-silico drug discovery tools, especially the databases of biochemical information they make use of, are a starting point of a "high level of achievement". When put in the hands of PHOSITAs of drug design and pharmacology, are any useful drugs discovered and tested ... just ordinary inventions that are will be ruled unpatentable under 35 USC 103 - YES or NO?

      Sadly, the legal thinking in this area is either non-existent, or idiotic. One of the few papers I found is from 2011: "Experimental evidence to support a patent application: are in-silico data enough?" - ( http://www.future-science.com/doi/full/10.4155/fmc.11.70), written by two Australian patent lawyers, talks all about the utility requirement, but nothing about the inventive-step/obviousness argument. A paper in Nature Biotechnology from 2004 is a nice review of these patent issues about 10 years ago (before KSR and Mayo): "Patent protection for protein structure analysis" - ( http://www.nature.com/nbt/journal/v22/n1/full/nbt0104-109.html), but we desperately need an update since drug discovery tools have become more powerful and obvious attacks more idiotic. Another review article, but again out-of-date (from 2011), is "Patenting the tools of drug discovery" - ( http://www.ddw-online.com/summer-2001/p148569-patenting-the-tools-of-drug-discovery.html>).

Note: these may be somewhat weak obvious arguments, but keep in mind that they are genius compared to the nonsensical logic becoming the fundamental tool of the CAFC. So if they can use a semi-nonsensical argument, or better a senisble argument, to destroy a whole class of drug patents, let the killing begin. If Judge Mayer can destroy a patent with an idiotic argument "The claim is not patentable because it is entrepreneurial, not technological." - a completely nonsensical statement - how easy will it be for him to reject a drug patent saying "The claim is not patentable because it is the obvious result of a PHOSITA using his drug discovery tools." I suggest immediately that PhRMA hire Reines, and give him a lot of money to "influence" the CAFC - maybe buy some tickets for Mayer to the Army/Navy game.

      From the point of view of patent insurance, I can go either way with the answer to this question. If the answer to the question is YES, then we can write Patent Defense Insurance policies (protecting companies from being sued for infringement) with low premiums, knowing that we will be able to kill such patents in court under 103, and collect attorneys fees because it is obvious (and therefore abusive) that all such patents are invalid.

      If the answer is NO, does this issue provide one ground for standing to start arguing the unconstitutional vagueness of 35 USC 103? The statute was born defective, when in 1952, Congress refused to define "obvious" in statute, and defined it circularly in the Legislative History (something is obvious if it has a great difference from the prior art, and it has a great difference from the prior art if it is ... not obvious). Fourteen years later, in Graham v. Deere, the Supreme Court created its test for obvious - "Something is obvious if you do some obvious things to prepare for an obvious analyze, then analyze if it is obvious" - THATS ALL THAT GRAHAM STATES, plus threw in some secondary considerations. The complete uselessness of 35 USC 103 in 1952, Graham in 1966 can be seen in the further confusion the Supreme Court created in 2007 with its KSR decision, which resolved nothing while adding a new undefined term "predictable".

      So I am tempted to have written a few cheap Defense Insurance policies, so there are grounds to go into court and argue either position - all of these patents are invalid for being obvious, or all of these patents are not obvious because it is obvious that "obvious" in patent law is constitutionally vague.

      Any thoughts would be appreciated, to help me prepare my talk. What follows is links to recent articles on in-silico drug discovery.

In silico machine learning methods in drug development,
Curr Top Med Chem, Nov. 2014

The biopharmaceutics risk assessment roadmap for optimizing clinical drug product performance,
J. Pharm. Sci., Nov. 2014

Virtual screening - an in silico tool for interlacing the chemical universe with the proteome,
Methods, Sep. 2014

Progress in the analysis of multiple activity profile of screening data using computational approaches,
Drug Dev Res, Aug. 2014

Evaluating protein-protein interaction networks for disease pathways, target discovery and drug-design using in-silico pharmacology,
Curr. Protein Pept Sci, Aug. 2014

In silico target fishing: addressing a "big data" problem by ligand-based similarity rankings with data fusion,
J. Cheminfom, Jun. 2014

Greg Aharonian
Internet Patent News Service
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