Precision medicine: an approach to R&D for delivering superior medicines to patients

Precision Medicine [1, 2] is an approach to discovering and developing medicines and vaccines that deliver superior outcomes for patients, by integrating clinical and molecular information to understand the biological basis of disease. This approach leads to better selection of disease targets and identification of patient populations that experience better clinical outcomes. Ultimately, the potential of Precision Medicine is that it will yield treatments that deliver clinically significant treatment effects, with favorable safety profiles. When appropriate, these new treatments are focused on a particular sub- group of patients with certain genotypic and/or phenotypic characteristics that make them more likely to benefit or less likely to experience side effects. A related concept, “Personalized Medicine”, has been defined by President’s Council of Advisors on Science and Technology (PCAST) as “the tailoring of medical treatment to the individual characteristics of each patient to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment [3]”. Thus, products and diagnostics developed through Precision Medicine facilitate the practice of Personalized Medicine.

Precision Medicine success is predicated on the appropriate selection of projects that benefit from its application, ideally fulfilling the following criteria:

· Strong human biology data package with evidence that the drug target is a critical driver of disease and its modulation is likely to produce a meaningful clinical benefit.

· Evidence of downstream pharmacodynamic effects as a consequence of target engagement.

· Biomarkers predictive of clinical benefit (both for efficacy and safety/toxicity) to allow population stratification and associated diagnostic markers if appropriate.

The development of biomarkers - some of which may ultimately translate into companion diagnostics - is a fundamental requirement to enable Precision Medicine. Broadly speaking, biomarkers can be categorized in terms of disease, mechanism or outcome. Those that are prognostic of disease progression or predictive of outcome will form the basis of companion diagnostics. It is critical to develop biomarkers at the earliest stages of drug discovery and, where based on preclinical models, translate them effectively into the clinic. The development of biomarkers to segment diseases into better understood molecularly-characterized subtypes depends on access to well-defined patient populations and patient biologic samples along with longitudinal clinical data and medical and treatment histories. Clinical trials or methodology studies will be required not only to demonstrate fit-for-purpose validation or qualification of specific biomarker candidates, but also to identify new biomarker candidates related to treatment outcomes, which in turn can be used for early research purposes. The development of a comprehensive biomarker plan at the very early stages (e.g. lead development) of drug development enables the generation of appropriate pre-clinical and translational markers and delivery of a qualified, fit-for-purpose biomarker to be incorporated into clinical trials.

Like therapies, biomarkers are validated in clinical trials. A typical biomarker is first evaluated in Phase I/II clinical trials. If the preliminary data indicates a clinically significant difference in outcome for patients based on a given biomarker, its predictive utility needs to be confirmed (replicated) in a prospectively designed study. A clinically significant improvement in outcome (therapeutic index) would be required for the biomarker to be validated for use in patient selection. Some of these biomarkers may be translated into a companion diagnostic that can be used to identify an appropriate subpopulation that should (or should not) receive treatment. Ideally, a drug and its companion diagnostic would be developed contemporaneously with the clinical relevance and technical performance criteria established using data from the clinical development program before NDA filing.

The ultimate end product of any R&D program is data that can support regulatory and intellectual property filings, inform a product label and support the manufacture and sale of the drug. Generation and advanced analysis of molecular and clinical data from studies are primary enablers for Precision Medicine decision making. Internal and external information can support and define decisions regarding target selection, pre-clinical and clinical experiment design, biomarker identification, disease modeling, and patient stratification. A wealth of human biology insight may be found in clinical, medical and basic biology data sets in academia and in pharmaceutical companies. These data are obtained from a range of resources including clinical trials, electronic medical records, personal health records, ‘omics’, sequencing and genotyping experiments. Opportunities exist to develop shared industry solutions relating to validation of markers, and to collaborate with commercial and not-for-profit entities on bio-specimens, clinical data, registries and other data relating to human biology.

Advances in lab technology over the last 10 years have increased the scale of internal and external data generation and increased the relevance to pharmaceutical companies. This trend will continue providing increasingly granular insight into the molecular drivers and correlates of clinical outcomes. Biomarker technologies that generate quantitative data, can be performed on small amounts of tissue (e.g. tumor biopsies), are multiplexable and/or allow for in vivo or minimally invasive assessment are particularly attractive.

Precision Medicine will hopefully lead to scientifically selected, well-defined populations enriched for responders, enabling smaller databases to support efficacy. The appropriate selection of patient populations for clinical trials has the potential to lead to earlier regulatory submissions, shorter and more predictable timing to approvals, and faster and more focused product launches. A higher rate of new drug approvals may also be expected due to stratification of populations when efficacy or risk considerations differ in various subpopulations, resulting in more compelling overall product risk/benefit (therapeutic index) versus current therapies, and better odds of approval. These benefits, however, come with some challenges. First, labels will be more narrowly crafted to focus the approved indication on the appropriate population . In addition, the regulatory pathway of novel therapies developed through Precision Medicine may be complicated by the accompanying selection method by which the population is defined. If a novel biomarker is to be used, and the product’s labeling defines the approved population by this measure, regulations require that the means of measuring the biomarker be commercially available. Increasingly, this is driving simultaneous drug and companion diagnostics development programs.

Precision Medicine requires careful evaluation of the commercial and market access landscape to accurately identify the commercial opportunity. Therapies developed through Precision Medicine may command a higher price and greater reimbursement, driven by enhanced value of therapy to patient and payer, improved patient compliance and increased level of trust and confidence among all stakeholders and reduced number of failures. In addition, there may be fewer adverse events and therefore less potential for market withdrawal and fewer label restrictions. However, these advantages are balanced by a more focused and fragmented market that might limit sales potential.

For these reasons, it is important to build a strong case for the medicine’s clinical benefit and therapeutic index in the defined patient population. Such a case could be supported through health economic considerations and/or health technology assessments which are increasingly being used by public health bodies to make recommendations on reimbursement of medicines and devices. From a payer perspective, there are many benefits of Precision Medicine that enhance the value proposition. These include better risk estimation and treatment optimization, diagnostics that can screen high risk patients to identify a specific disease early, and tests that provide healthcare providers and payers with a broad risk profile for a specific disease to identify appropriate patients for a given targeted therapy. Importantly, the ability to identify those patients who will have higher treatment response rates and will experience fewer adverse events and/or side effects will serve as a powerful driver of value as payers balance increasing healthcare costs against healthcare funding constraints and shrinking budgets. Payers are wary of covering diagnostics when there is a not a clear link to a health economics or treatment benefit, so the scientific and commercial rationale for its use must be sound.

Appropriate handling of the ethical and legal challenges for clinical trial investigators, regulatory authorities, patients, payers and other stakeholders that arise out of Precision Medicine is imperative to increase public confidence, the viability of data collection efforts and successful commercialization of personalized medicine products. A key area relates to privacy, confidentiality and patients’ rights issues, and the evolving ethical issues around collection of samples and data for future, “secondary” research that could involve new subpopulations, biomarkers, and other indications relevant to Precision Medicine. An additional consideration is the legal uncertainty regarding patentability and enforceability of personalized medicine method claims, which seek to cover the two-step process of determining the level of a biomarker (e.g., metabolite) in a diagnostic test and then administering the appropriate medication).