Pharmaceutical and biotechnology companies spend billions of dollars in drug discovery every year. Despite continuing commitment of extraordinary financial and personnel resources, an alarming proportion of oncology drugs continue to fail during clinical development. A number of causes are likely to account for high clinical failure rates, including (1.) a core discovery focus on preclinical models that poorly reflect complexities of human disease and (2.) an inadequate integration or understanding of translational biomarkers. These shortcomings, coupled with patent expirations, have created substantial revenue pressures. As a result, the pharmaceutical industry has derisked internal research through increased external investments in smaller partner companies who have novel drugs, drug targets or innovative discovery approaches. This approach has already yielded solid results and is exemplified by the emergence of immune targeted agents for cancer, most of which emerged from academic spin-offs and smaller biotechnology companies.
BioArkive has a long (>20 years) track record in working with advanced 3D tumor models that provide novel translational insights on prospective oncology drug candidates. Unlike BioArkive’s tumor microenvironment (TME)-aligned 3D models, the industry standard for drug screening, more often than not, inadequately mirrors relevant human tumor physiology. Some examples of poorly modeled attributes of human cancer include:
Biopharma’s reliance on outdated, 2-D tissue culture systems has yielded a skewed oncology drug market that is enriched for toxic drugs that disrupt cell proliferation and survival, due to biology that is artificially enhanced in traditional 2D tissue culture. Why has biopharma failed to more widely adopt accepted tenets of human TME biology? There are likely several reasons for slow adoption of TME models throughout the early drug discovery process: (1) Bureaucratic challenges inherent in large organizations limit integration of new biologic paradigms, (2) Conflict resolution across multiple ongoing and parallel drug discovery programs at varying stages of preclinical development (e.g., challenges to integrate novel methods and resolve contradictory data from evolving models), (3) Aversion to risk taking, even when supported by an expanding body of evidence dating back to well over two decades, and (4) an entrenched need to observe equivalence across TME-aligned and non-aligned models (e.g., dogma).
As your partner in 3D tumor modeling, we can help support your innovative TME modeling needs that will enable you to deliver IND-stage assets in a faster and more cost-effective manner. Furthermore, we believe that emerging drug candidates, developed in human-aligned models, will be enjoy greater translational success in the clinic. BioArkive’s competitive advantage lies in our adherence to supporting your human TME-aligned modeling needs during the entire drug development process.