Bits, Bytes and Biology: A new paradigm for designing therapies

Pradeep Fernades, co-founder and President of Cellworks Group (, discussed new derisked and innovative approach to developing therapies with enhanced probability of success at .


This new approach based on integrating biology and computing, enables a new paradigm that dramatically can reduce spending for developing new therapies.  Currently $100B is spent globally, each year for pharmaceutical R&D.  The cost for development of each new drug is estimated to be between $1 to $4B, depending on how the math is done.  While published research and data is exploding, the overload of information makes it increasingly challenging to meaningfully use the information.  The pharmaceutical industry is pouring more and more money into the R&D and increasingly has lesser probability of success.  Problem is that despite the technology advancement, the drug development process remains fundamentally unchanged and drug development is validated very late in clinical trials.  Real understanding of drugs is only possible during clinicals and even then the underlying mechanism of action if frequently unclear.


Informatics can bridge the gap and improve the outcomes, both better consumer oriented information that include monitoring of patient, drug, and trends as well as development oriented information that includes information about genomics, proteomics, biology etc.  Cellworks Group is focused on development oriented informatics, which have traditionally been aimed at leveraging information technology and software algorithms to help manage large data sets, extract information from large data sets, and allow visualization of data.  Their engineering model further goes from analyzing and extracting information to predicting information through abstraction modeling, simulation, and synthesis.  This is contrary to traditional model where biologist begins at the lab, puts the drug in and if there is expected effect, then the initial hypothesis is confirmed which does not frequently happen.  In this model, based on mathematical modeling, equation at each interaction within the cell, is analyzed and understood.  This is a predictive computational disease model based on integrating insights of thousands of scientists, research data, experimental protocols, and clinical trends, that is mathematically observed at cellular level.  Fernandes shared several ongoing collaborations and validations in oncology, rheumatoid arthritis, and anti-infection that are under way.


Essentially this is a process for finding innovative new therapies that begins with very explicit assumptions. It is based on leveraging functional representation of biology using mathematics.  Relationship of each interaction is represented using differential equations.  It emulates human disease physiology computationally and integrates it with understanding biological efficacy and toxicity.  The process enables prediction of clinical outcomes as well as novel non-obvious insights and is many times speedier than wet approaches.  It is about time that these new approaches be explored so that drug development process goes through an overhaul rather than small, incremental enhancements to make it more cost-effective.

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