Pune, India

30th March 2019


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Data Science (Past, Present, Future)


Currently, data science is the most discussed topic in every segment of industry. The core of data science is about uncovering findings from data to help us make smarter business decisions, i.e. deep diving into the granular level to mine and understand complex behaviours, trends and inferences. Due to the generation of vast data, coupled with advancement in technology, the data science stream has been evolving at a fast pace. If we consider data science as a function of time, then it is interesting to understand where it came from and the direction in which it is headed.

Specific to the pharma industry, there is a growing pressure to improve overall productivity and reduce development time to maximize the period of patent protection so that R&D costs can be recovered. The drug development process is extremely complicated and multidisciplinary and therefore no overall model serves as a basis for optimization and improvement. Pharmaceutical companies are generating increasing amounts of data and, as a result, the value of the data scientist. There is a growing belief that data science and approaches from engineering and computer science will be critical for the long-term future of the industry. Across the industry, expectations on using technology-driven solutions are increasing and investments in applying artificial intelligence, machine learning and automation to drug development use cases are also taking a leap. While technology is making progress, the skills requirement of the workforce is also going to evolve. The industry has started talking about data managers being tomorrow’s data curators and statistical programmers being data analysts; and all this will lead to building skills to meet forthcoming job roles. There are visionary organizations moving with agility towards embracing these changes and preparing for the future work environment.


Conference Room: Rectangle A

The O Hotel
Koregaon Park
North Main Road
Pune 411001

Tel: 020-40011000


08:15 - 09:15 Registration and Welcome Refreshments  
09:15 - 09:45 Welcome and Overview of PhUSE Sarvesh Singh,
PhUSE APAC Director
09:45 - 10:30 AI in Pharma – Myth or Reality! Sowmyanarayan Srinivasan,
10:30 - 11:15 Reaping The Fruits of Clinical Research Tree Using AI and ML Dinesh Pillaikamant,
Sineflux Solutions
11:15 - 11:30 Coffee Break
11:30 - 12:00 The Use of Data to Find Efficiencies in Drug Development – Getting the Most out of Wearable Technology in Clinical Research Supriya Deshmukh,
Syneos Health
12:00 - 12:30 Building Bridges – The Paradox of Big Data in Pharma Aruna Chakraborty,
12:30 - 13:00 Evolution of Statistical Methodologies in Clinical Trials Namita Shinde,
13:00 - 14:00 Lunch Break
14:00 - 14:30 Allegory of Prudent Data Science Subbiah M,
Acroama Gnan Vikas
14:30 - 15:00 Observational Study: Journey of Film Without Dialogues in Superhit Movie Seema Shah,
15:00 - 15:30 Data Science in Pharmaceutical Industry – An Introduction Bhakti Patil & Atul Karve,
15:30 - 16:00 Explainable AI – Moving AI from Black Boxes to Glass Ones Munshi Imran Hossain,
16:00 - 16:15 Coffee Break
16:15 - 17:15 Panel Discussion and Q&A

Dinesh Pillaikamant,
Sineflux Solutions

Subbiah M,
Acroama Gnan Vikas

Nitin Pawar,
Syneos Health

Devi Gopalakrishnan,

Sowmyanarayan Srinivasan,

Arjun Roy,
Karmic Life Sciences

17:15 - 17:30 Wrap-up and Closing Remarks Sarvesh Singh,
PhUSE APAC Director


SDE Chair:

Nikita Agnihotri, GCE Solutions

Swapna Deshpande, Cytel

If you have any questions, or require any information, please contact the SDE Chairs.








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