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Digital tools hold potential to reshape formulation in pharma

Experts at FABA workshop discuss AI’s role in drug development

Digital tools hold potential to reshape formulation in pharma
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Digital tools hold potential to reshape formulation in pharma

Hyderabad: On the day five of Federation of Asian Biotech Associations (FABA)-organised workshop on “Artificial Intelligence for Pharma and Biotech,” an expert session shed light on the hurdles faced in formulation development, setting the stage for a digital transformation. Dr Ramesh Rachapudi from Dr Reddy’s spoke on “Transforming Formulation Challenges with Cutting-Edge Tools.”

The workshop is being held in partnership with Science Gurus, University of Hyderabad and World Trade Center Shamshabad. The ongoing event will come to an end on December 16, 2023.

Dr Rachapudi said that adoption of digital platforms prompts essential questions, including the capability to screen from a vast array of IIG-listed excipients without lab dependency. He walked the audiences through two case studies where FormDEM, a leading digital tool, successfully addressed formulation challenges. He further said that the ability to deeply understand and swiftly formulate has the potential to reshape pharma by introducing time-saving tools. This innovative approach signals a pivotal shift towards efficiency, precision, and a future where digital tools redefine the landscape of pharmaceutical formulation.

The next session commenced with speaker Dr Pritesh Bhat, Schrodinger delivering a talk on “Discovering drug molecules using the Schrodinger Platform- overview and case studies.” Dr Bhat highlighted the Schrodinger digital chemistry strategy, underscoring its consistent delivery of high-quality therapeutic drug candidates. He emphasised that the advantages of ML-based methods include speed, effectiveness in interpolation, and the capability to handle vast databases. The following session led by Dr Koushik Kasavajhala, Schrodinger on “Leveraging machine learning applications combined with physics-based modeling for drug discovery.”

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