Drug Discovery, Clues from the Clinic

Dr. John LaMattina, former R&D President at Pfizer, has declared new drug development to be “stochastic” – and for good reason. Only one drug in nine succeeds through the long, costly process of clinical trials.  For cancer, only one drug in twenty makes it to market. These numbers echo the relative success of “drug targets” in clinical trials:  only one out of ten drug targets tested in the clinic have proven successful. The dominant pre-clinical, drug “discovery” paradigm, “Target-Based” discovery (and its reliance on genetics), is increasingly cited as a cause of declining drug development effectiveness.  Garbage IN – Garbage OUT?

Repurposing clinically successful targets

Regardless of the probable flaws of Target/Genetics-based discovery, clinical outcomes may represent a crucial source of information for pre-clinical drug discovery.  Can, for example, the 10% of clinically successful targets inform pre-clinical drug candidate selection?  Are there actionable traits or properties common to successful targets?  Must drug development remain stochastic?  Answering these and similar questions are the objective of this posting.  As will become clear, “Clues from the Clinic” point directly to the intersection of drug and disease biology.  Equally important, those “Clues” also define a sorely needed alternative to gene-driven drug discovery – discovery based on the pragmatism of phenotype.

A great deal of legwork appears in a publication in 2006, updated through 2014.  Among other analyses, this work examines clinical outcomes for trials with “known” targets.  First, the data indicate that multiple diseases can be ameliorated through modulation of common targets, i.e. drug targets are disease-promiscuous. Looking, for example, at “Circulatory System Diseases,” over 45% of “successful” targets are common with “Nervous System . . .”, 25% with “Respiratory System . . .” and 35% with “Neoplasms” (cancer).  Within the context of Target-Based discovery, the work appears to reinforce the observation that drug development is, indeed, random.  There is, fortunately, order in this apparent chaos as shown by analysis performed at New Liberty Proteomics (NLP).
Repurposing clinically successful targets

Role of plasma membrane in drug discovery

Two out of three “Market-Proven Targets” operate at or near the plasma membrane.  This is the bottom-line analysis of fundamental data collected for “successful” targets from a variety of online resources (e.g. Uniprot).  Of data collated in nine separate categories and 34 parametric entries, sub-cellular location proved to be the unifying factor.  Biologically these data reinforce the importance of fundamental events, e.g. cell-cell communication, receptor activation, and intracellular response.  The data also reflect well known problems associated with drug delivery to intracellular locations such as nuclei or mitochondria.  Recalling that targets are apparently disease-promiscuous, these data also point toward multiple means of achieving common results via modulation of diverse intracellular networks.  Finally, these data suggest a new, perhaps necessary, drug discovery approach.

Role of plasma membrane in drug discovery

Action/ reaction model (ARMetric)

The locus of successful drug activity suggests an Action/Reaction model for discovery.  Extracellular entities such as cytokines interact with and modulate the behavior of intra-membrane entities such as receptors and transporters.  This modulation, in turn, is the precipitating event for promotion or inhibition of intracellular binding by, e.g., G-proteins.  Dubbed “ARMetric” for “Action/Reaction,” drug candidates can be screened for their ability to modulate extracellular activity at the plasma membrane and reaction at the intracellular membrane surface.  Indeed drug candidates should be screened for multiple actions and reactions for general analysis of the candidate’s “polypharmacological” activity and potential for multiple disease efficacy.  If performed in intact cells or tissues, the pathway is open for concurrent drug evaluation, determination of a drug’s “mechanisms of action” and “companion diagnostic” selection of patients based on drug-selective, phenotypic criteria.

Action/ reaction model (ARMetric)

One specific example of extracellular “Action” is the interaction and interaction modulation of the inflammatory cytokine, Interleukin 1a (Il1a).  Il1a initiates an inflammatory response through binding to its receptor.  Binding of the cytokine can be modulated by both the antagonist and antibody, though through different mechanisms (the antagonist and antibody are functional analogues for recently approved Il1a inhibitors).  NLP’s methods encompass the ability to quantitatively assess all interactions, modulation of those interactions on intact cells or tissues via a novel application of electron magnetic resonance spectroscopy and “spin” labeling.

interaction and interaction modulation of the inflammatory cytokine, Interleukin 1a (Il1a).

Impact ARMetric could make to drug discovery and future directions:

This specific example of Action-side interactions is, in general, representative of all receptor-mediated plasma membrane activity.  All include activation of the receptor and naturally occurring modulators of that activation.  Thus a suite of Actor/Receptor/Reactor groups can be selected that are disease-specific or disease-opportunistic – or both.  The impact of other bio-relevant entities such as hormones, metabolites, metal ions – or other drugs- is readily appraised.  The same is true for multiple mechanisms of action for drug candidates, including mechanisms that presage side effects and/or toxicity.  Moreover, each Action/Reaction appraisal is a potential candidate as an Action-Driven biomarker.  Likewise, each mechanism manifest by a drug candidate is a potential biomarker for Companion Diagnostics.

ARMetric is clearly “holistic” and “high content.”  It integrates the whole of drug discovery, determination of mechanisms of action, and development of biomarkers required for companion diagnostics and subsequent selection of patients – all within the lower-cost period of pre-clinical development.

Order from Chaos.

What are your views on the future of drug discovery and what can be done to increase success rates? Is ARMetric one such way?

Please share comments below.

Ray Perkins

Dr. Ray Perkins is Founder and President of New Liberty Proteomics Corp, a Contract Research Organization whose unique mission is integration of Drug and Diagnostics development in support of Personalized (Precision) Medicine. Anticipating the failure in genomics-driven approaches, NLP assesses the impact of disease and drugs on fundamental molecular and cellular activity.

Dr. Perkins earned a PhD from Vanderbilt University where he was a research fellow for the Muscular Dystrophy Association, adapting magnetic resonance technologies to assessment and diagnosis of disease. Those capabilities were expanded through experience in the scientific instrumentation industry with roles in application development, instrument design and international marketing.

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