Connecting Insights

This report explores how connecting disparate streams of data can create valuable insights that can make the difference in today’s biopharmaceutical marketplace. While these opportunities for connections exist across all disease and therapeutic areas, they may be most acutely needed in the complex and dynamic area of oncology. This report makes the case for the process by which a looming crisis in oncology can be averted, by applying the science—and art—of connecting healthcare insights.

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Summary

The future of medicine rests on data. Data, and the analysis of that data, informs drug development, portfolio decisions, prescribing behaviors, patient compliance and reimbursement policy in value-based healthcare systems. The past decades have proven the utility of appropriately curated evidence in improving efficiency and efficacy in clinical development and market access, and perhaps more importantly, in providing actionable insights for the constellation of stakeholders across the healthcare spectrum.

The biopharma industry has invested in and benefited from the explosion of data and analytics tools that together comprise the core of the evidence packages that continue to drive drug value, but substantial evidence increasingly resides outside the data collected by biopharmaceutical sponsor companies. It is when these disparate data streams are applied to clinical interventional and observational research that a new construct for the development and commercialization of the next generation of medicines becomes clearer. This paper aims to demonstrate that the tools and the process to reach the full potential of this approach already exist, exploring the specifics of how the pieces can be put together, what the tools are, and what applications need to be developed.

Key Findings

Genetic Information Has Led to Rapid Advances in Targeted Therapies

  • More than 700 New Active Substances have entered the healthcare system since 1996 driven by industry use of new technologies, access to rich data sources, and advances in scientific discovery related to biomarkers and genomic research
  • An increase in the availability of patient and genetic information is moving drug development toward more personalized treatment of the patient— in oncology alone, 71 drugs have launched with pharmacogenomic biomarkers
  • These advances are also adding complexity and cost to the drug development process

Targeted Therapies Are Contributing to Increasing Oncology and Supportive Care Costs (US$Bn)

  • Globally, total sales of medicines used as oncology therapeutics and for patient supportive care have increased from $90 billion in 2011 to $107 billion in 2015
  • In the U.S., 11.5% of total drug costs are now accounted for by oncology treatments, up from 10.5% in 2011

Payer Evidentiary Demands for Proof of Value Are Contributing to Increasingly Complex Clinical Trials

  • The total number of endpoints needed in clinical trials has doubled since 2002
  • A 61% increase in the number of eligibility criteria, and competition for smaller target patient populations, have contributed to a decrease in patients randomized into clinical trials by an average of 18% from 2002-2012
  • Biopharma sponsors are having to think more strategically about the cost, time, operational feasibility and productivity of clinical trials as complexity and the total cost of development of therapies continues to go up year-over-year

Real-World Data Can Inform Tumor Target Selection and Reduce Clinical Trial Complexity

  • In oncology, biopharma companies increasingly address this complexity by leveraging data sources, including real-world data, to measure patient populations in complex settings and using advanced analytics to bridge gaps in data availability
  • Real-world data supports clinical as well as commercial decisions - such as selecting tumor targets - by allowing sizing and segmenting patient pools with high commercial viability and clinical unmet need, identifying undiagnosed and latent patient pools in niche areas; identifying patient segments based on risk predictors; and prioritizing of indications for asset development

Data Can Be Harnessed Broadly to Provide Solutions Across Clinical Research, Patient Care and Commercial Value

  • Biopharma can adapt to a more dynamic development environment by applying data across the biopharma value chain
  • Data can reduce uncertainties associated with biopharma decision-making, including candidate selection and the design and optimization of clinical studies, help companies to demonstrate the value of new medicines to healthcare stakeholders, and help optimize patient care

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