An evaluation of regulatory and commercial barriers to stratified medicine development and adoption

Dielectrophoretic analysis of treated cancer cells for rapid assessment of treatment efficacy

Whilst personalized medicine (where interventions are precisely tailored to a patient's genotype and phenotype, as well as the nature and state of the disease) is regarded as an optimal form of treatment, the time and cost associated with it means it remains inaccessible to the greater public. A simpler alternative, stratified medicine, identifies groups of patients who are likely to respond to a given treatment. This allows appropriate treatments to be selected at the start of therapy, avoiding the common "trial and error" approach of replacing a therapy only once it is demonstrated to be ineffective in the patient. For stratification to be effective, tests are required that rapidly predict treatment effectiveness. Most tests use genetic analysis to identify drug targets, but these can be expensive and may not detect changes in the phenotype that affect drug sensitivity. An alternative method is to assess the whole-cell phenotype by evaluating drug response using cells from a biopsy. We assessed dielectrophoresis to assess drug efficacy on short timescales and at low cost. To explore the principle of assessing drug efficacy we examined two cell lines (one expressing EGFR, one not) with the drug Iressa. We then further explored the sensitive cells using combinations of chemotherapeutic and radiotherapeutic therapies. Our results compare with known effects of these cell/treatment combination, and offer the additional benefit over methods such as TUNEL of detecting drug effects such as cell cycle arrest, which do not cause cell death.

Key elements of metabolomics in the study of biomarkers of diabetes

Metabolomics is instrumental in the analysis of disease mechanisms and biomarkers of disease. The human metabolome is influenced by genetics and environmental interactions and reveals characteristic signatures of disease. Population studies with metabolomics require special study designs and care needs to be taken with pre-analytics. Gas chromatography coupled to mass spectrometry, liquid chromatography coupled to mass spectrometry or NMR are popular techniques used for metabolomic analyses in human cohorts. Metabolomics has been successfully used in the biomarker search for disease prediction and progression, for analyses of drug action and for the development of companion diagnostics. Several metabolites or metabolite classes identified by metabolomics have gained much attention in the field of diabetes research in the search for early disease detection, differentiation of progressor types and compliance with medication. This review summarises a presentation given at the 'New approaches beyond genetics' symposium at the 2015 annual meeting of the EASD. It is accompanied by another review from this symposium by Bernd Mayer (DOI: 10.1007/s00125-016-4032-2 ) and an overview by the Session Chair, Leif Groop (DOI: 10.1007/s00125-016-4014-4 ).

Economic viability of Stratified Medicine concepts: An investor perspective on drivers and conditions that favour using Stratified Medicine approaches in a cost-contained healthcare environment

RATIONALE

Stratified Medicine (SM) is becoming a natural result of advances in biomedical science and a promising path for the innovation-based biopharmaceutical industry to create new investment opportunities. While the use of biomarkers to improve R&D efficiency and productivity is very much acknowledged by industry, much work remains to be done to understand the drivers and conditions that favour using a stratified approach to create economically viable products and to justify the investment in SM interventions as a stratification option.

CONCEPT

In this paper we apply a decision analytical methodology to address the economic attractiveness of different SM development options in a cost-contained healthcare environment. For this purpose, a hypothetical business case in the oncology market has been developed considering four feasible development scenarios.

CONCLUSIONS

The article outlines the effects of development time and time to peak sales as key economic value drivers influencing profitability of SM interventions under specific conditions. If regulatory and reimbursement challenges can be solved, decreasing development time and enhancing early market penetration would most directly improve the economic attractiveness of SM interventions. Appropriate tailoring of highly differentiated patient subgroups is the prerequisite to leverage potential efficiency gains in the R&D process. Also, offering a better targeted and hence ultimately more cost-effective therapy at reimbursable prices will facilitate time to market access and allow increasing market share gains within the targeted populations.

A Quantitative Assessment of Factors Affecting the Technological Development and Adoption of Companion Diagnostics

Rapid innovation in (epi)genetics and biomarker sciences is driving a new drug development and product development pathway, with the personalized medicine era dominated by biologic therapeutics and companion diagnostics. Companion diagnostics (CDx) are tests and assays that detect biomarkers and specific mutations to elucidate disease pathways, stratify patient populations, and target drug therapies. CDx can substantially influence the development and regulatory approval for certain high-risk biologics. However, despite the increasingly important role of companion diagnostics in the realization of personalized medicine, in the USA, there are only 23 Food and Drug Administration (FDA) approved companion diagnostics on the market for 11 unique indications. Personalized medicines have great potential, yet their use is currently constrained. A major factor for this may lie in the increased complexity of the companion diagnostic and corresponding therapeutic development and adoption pathways. Understanding the market dynamics of companion diagnostic/therapeutic (CDx/Rx) pairs is important to further development and adoption of personalized medicine. Therefore, data collected on a variety of factors may highlight incentives or disincentives driving the development of companion diagnostics. Statistical analysis for 36 hypotheses resulted in two significant relationships and 34 non-significant relationships. The sensitivity of the companion diagnostic was the only factor that significantly correlated with the price of the companion diagnostic. This result indicates that while there is regulatory pressure for the diagnostic and pharmaceutical industry to collaborate and co-develop companion diagnostics for the approval of personalized therapeutics, there seems to be a lack of parallel economic collaboration to incentivize development of companion diagnostics.

Personalized medicine for gastroenteropancreatic neuroendocrine tumors: a distant dream?

Neuroendocrine tumors are heterogeneous cancers that can present with advanced disease. Treatment stratification is often based on limited characterization of tumor behavior from histological grade and imaging assessments. Personalized medicine strategies focus on tailoring therapy through characterization of cancer pathways and the development of biomarkers. This review article explores the current personalized medicine landscape in gastroenteropancreatic neuroendocrine tumors, from tissue and circulating biomarkers development through to tumor heterogeneity and reimbursement issues.

Pharmacogenetic Markers of Drug Efficacy and Toxicity

The action of a drug is dictated by its pharmacokinetic and pharmacodynamics properties, both of which can vary in different individuals because of environmental and genetic factors. Pharmacogenetics, the study of genetic factors determining drug response, has the potential to improve clinical outcomes through targeting therapies, individualizing dosing, preventing adverse drug reactions, and potentially rescuing previously failed therapies. Although there have been significant advances in pharmacogenetics over the last decade, only a few have been translated into clinical practice. However, with new rapid genotyping technologies, regulatory modernization, novel clinical trial designs, systems approaches, and integration of pharmacogenetic data into decision support systems, there is hope that pharmacogenetics, as an important component of the overall drive towards personalized medicine, will advance more quickly in the future. There will continue to be a need for collaboration between centers all over the world, and multisector working, capitalizing on the current data revolution.