Chennai, India

12th October 2019

Faster Access to New Medicine – Cutting Down the Development Life Cycle by 25%: Is That a Dream or a Reality?


New advancements in the clinical world are leading to a drastic shift in the way drugs are developed. There has not just been a change in what research yields: the conduct and the efficiency of how research and development happen in today’s world has also seen progress. The number of years that would be spent in the lab a decade ago to identify one target out of many such molecules, and then further during its development right through to marketing, in comparison with global demand, needs review and thought as to how can we do this better. Sponsors are under tremendous pressure to meet the demands of the market and competition, trying to balance out the cost of development to ensure faster access to patients. With technology advancing into the age of artificial intelligence, faster and better solutions are available, yet we need to know how better to utilize them to our benefit.

So, what ideas do we have as a research industry to do better, faster and smarter? As contributors to the drug development organization, are we able to contribute to this need in our own way? How about efficient systems and tools to do data cleaning activities, or reducing the number of reports generated for an analysis? What can we each do to bring down cycle times and reruns of the same data repeatedly? Or is all this just a mere dream? Is it even close to becoming a reality? Let us debate, discuss and, together, decide on what we can do! The time to think is NOW!



Going Digital in the Analysis & Reporting Space – Christopher J. Colangelo, Pfizer

Accelerate Drug Development Using AI & ML – Anoop Ambika, Genpro

Seamless Adaptive Phase II/III Clinical Trials: An Example of Significant Reduction in Development of a Small Molecule Compound in Oncology (Time, Sample Size and Costs) – Tommy Pedersen, Cognizant

Evolution or Revolution? From Vision to Decision – Pratibha Jalui, Cytel

A Stitch in Time Saves Nine – A Statistical Programmer's Perspective – Jayapandian Nagamalaiyan, Bayer

Reducing the Clinical Drug Development Life Cycle Through a Smarter Decision-making Framework Driven by Statistical & Probabilistic Measures – Sakthivel Sivam, GlaxoSmithKline

Towards Automating Statistical Programming – Ganesh Gopal, Ephicacy

Timeline Shift – Vijayakumar Radhakrishnan, ICON

RTOR – The Race is On – Dipti Patil and Hemangini Gurlani, PAREXEL


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