|Send to printer »|
Making Effective Regenerative Medicine Decisions
A targeted metric system could help in identifying potential, business-viable RM products.!--h2>
The field of regenerative medicine (RM), encompassing stem cell (SC) technologies, therapeutics, and tissue engineering (TE) provides a wide gamut of tools to combat, manage, and, hopefully, cure serious human and animal injuries, dysfunctions, and diseases.
Media hype and public expectations combined with divided trends and approaches among scientific, clinical, and business leaders have lead to time- and cost-ineffectiveness and unconsolidated outcomes.
Decision making is central to new drug development, which can be very costly, risky, and time-consuming especially for newer therapeutics and technologies such as RM.
Figure 1 schematically outlines the field of RM including different approaches, decision channels including public and private pathways, with technologies ranging from cellular-based approaches to tissue regeneration and organ building with further integration of acellular and scaffold/biomaterials components for diagnostic and therapeutic applications.
The RM field is rapidly evolving with a variety of adult and nonadult tissue resources and growing involvement of diversified players from academia, nonprofit, for-profit, regulatory, and government organizations.
RM has the capacity to address unmet clinical needs, and significantly improve on present therapies. These products will be developed as a result of therapeutic effectiveness, an adequate safety profile, and meeting regulatory requirements. The technology used in the products will dictate the development and manufacturing costs, the regulatory pathways, and the time taken to complete clinical trials, gain regulatory approval, and become commercialized.
All said, the RM portfolio is growing exponentially, but successful product outcomes are still difficult to predict. There is an ardent need for an effective metric system to identify and grade the probabilities, success potentials, and presumable pitfalls to validate RM treatments and technologies.
TEMPO Metric System
TEMPO metrics define five panels of grading parameters to help in predicting Go-No-Go decisions for investors and investigators. This approach utilizes data value points corresponding to (T) Translational capabilities, (E) Exclusivity in the Current and Emergent Market Spaces, (M) Manufacturing, Monetary, and Regulatory Hurdles, (P) Proprietary Exclusivity and challenges, and (O) Operational challenges.
Figure 2 illustrates the different internal and external directives and challenges that investigators and investors have to identify, analyze, and plan for an affirmative drug developmental pathway. Identifying the risk factors and how those can be encountered and effectively managed is one of the several equations to solve in this multilayered translation puzzle.
The challenge is to identify pathways to define a clearer winning technology/protocol using the different resources that are available in the public and privately accessible domains.
Figure 3 illustrates a theoretical, multi-component system where the RM therapeutic or technology in question is put through a scrutinizing pathway and analyzed on its potentials and pitfalls. Each designated panel within TEMPO has five subsets of independent-grading components. Grading within the subsets range from 0–3 (0 for poor performance and 3 for excellent performance) with 0 and 1 designated with a red X, 2 with an orange X, and 3 with a green X.
Scores are then added up and divided by five for the final tally, with scores 0–5 implying for weakest prospective, No-Go outcome. Scores 6–9 denote weaker prospect needing further scrutiny for a GO outcome and score from 10–15 suggests a clear “Go Ahead” prospective winner.
Defining, listing, assessing, and prioritizing tools for institutionalizing evidence-based Go-No-Go decisions for new process/product offerings are critical for business success and longevity. Such multiple perspective-based decision making can be valuable for initial qualitative analysis and further lead into bigger scope of quantitative business predictions.
As it is quite difficult defining health outcomes, cost-effectiveness decisions, and many other uncontrolled probables thrown in the pool of novel RM landscape, a targeted metrics system such as TEMPO can provide effective pathway determination and thorough, diversified assessment tools, and assist in identifying potential, business-viable RM products for effective time and cost development and management.
Abner M. Mhashilkar, Ph.D. (email@example.com), Ed Branson, Ph.D., and Anthony Atala, M.D., are at Wake Forest Institute for Regenerative Medicine.
© 2013 Genetic Engineering & Biotechnology News, All Rights Reserved