AI + Cheminformatics: The Future Career Formula for Drug Discovery & Pharma Innovation
Empowering Chemists with AI-Driven Skills for Modern Pharma Research
Date: 23rd October 2025
Time: 7:00 PM – 8:00 PM IST
Location: Online (Zoom)
Rasayanika successfully hosted the webinar “AI + Cheminformatics: The Future Career Formula for Drug Discovery & Pharma Innovation” on 23rd October 2025, an insightful session designed for students, researchers, and professionals keen to explore the transformative role of AI/ML in chemistry and pharmaceutical innovation. The one-hour live session brought together industry leaders and internal experts to provide a roadmap for building AI-ready skill sets that align with the evolving needs of the global pharma and biotech industries.
Welcome & Introduction
The webinar began with a welcome note by Mrs. Urmimala, who highlighted why AI and Machine Learning (ML) are revolutionizing modern biosciences. She emphasized the growing importance of practical AI/ML experience for research careers and introduced the speakers and session flow, setting the stage for a highly engaging knowledge-sharing session.
- Predictive Chemistry, Where Algorithms Meet Molecules
Speaker: Guest Speaker (External)
About the Speaker
The guest speaker is a leading professional in cheminformatics and AI-driven molecular research, specializing in predictive modelling and computational chemistry applications .
Session Highlights
The session explored the evolution of cheminformatics from basic molecular descriptors to advanced deep learning techniques. Key insights included:
- AI models that predict toxicity, reactivity, and bioactivity before experiments.
- Real-world applications: QSAR modelling, virtual screening, and molecular docking.
- Essential computational concepts: SMILES notation, molecular fingerprints, and graph-based models.
- AI tools empowering chemists: DeepChem, RDKit, and AlphaFold, enabling data-driven discovery rather than trial-and-error experimentation.
Attendees gained a clear understanding of how computational chemistry is accelerating drug discovery and why mastering AI tools is essential for modern chemists.
- The Industry Shift — How Pharma is Investing in AI & What It Means for You
Speaker: Dr. Snigdha Tiwari, Internal Faculty
About the Speaker
Dr. Snigdha Tiwari is an experienced professional in pharmaceutical R&D and computational sciences, specializing in AI integration for drug discovery pipelines.
Session Highlights
Dr. Tiwari provided real-world insights into the growing adoption of AI across global pharmaceutical companies:
- Industry Examples:
- AstraZeneca & Algen Biotechnologies – $555M AI + CRISPR partnership for immunology therapies.
- Takeda Pharmaceuticals – Hiring Associate Directors in Cheminformatics.
- Eli Lilly – Hyderabad Innovation Center to hire 1,500 AI & digital experts by 2026.
- AstraZeneca & Algen Biotechnologies – $555M AI + CRISPR partnership for immunology therapies.
- Global Hiring Trends: 41% YoY increase in AI/ML jobs in India.
- Emerging Roles: AI Chemist, Cheminformatics Data Scientist, Computational Chemist.
- Salary Trends & Demand: Opportunities growing in India and abroad.
Her session highlighted the importance of aligning skillsets with industry needs to secure high-impact roles in computational drug discovery.
- Becoming an AI-Ready Chemist — Skillset & Tools
Speaker: Ms. Shubhi Singh, Internal Faculty
About the Speaker
Ms. Shubhi Singh specializes in AI/ML applications in cheminformatics and in training chemists in computational methods, molecular simulations, and data-driven drug discovery techniques.
Session Highlights
Ms. Singh’s presentation focused on developing practical AI/ML capabilities for chemists:
- Core computational techniques: molecular representations, ML algorithms for QSAR & property prediction, molecular docking, and structure-based modelling.
- AI-based protein and ligand analysis tools.
- Skillsets in demand: data preprocessing, QSAR modelling, docking, Graph Neural Networks (GNNs), and molecular simulations.
- Transitioning from wet-lab to data-lab science: adopting programming, computational reasoning, and data interpretation.
- Future trends: generative AI, digital twins, and autonomous drug design platforms.
Attendees learned how to bridge traditional chemistry skills with AI-driven approaches to stay ahead in research and innovation.
Interactive Q&A and Closing Remarks
The webinar concluded with an engaging Q&A session moderated by Mrs. Urmimala. Participants clarified queries regarding AI tools, career transitions, and industry expectations. The session also introduced Rasayanika’s AI/ML in Cheminformatics Course, starting 28th October 2025, which offers:
- Hands-on experience with DeepChem, RDKit, DiffDock, AlphaFold, and HADDOCK.
- Guided mentorship and research projects (3/6/12 months).
- Certification, placement assistance, and resume/LinkedIn profile guidance
Key Takeaways
- AI + Cheminformatics is transforming the landscape of drug discovery and pharma innovation.
- Proficiency in predictive modelling, QSAR, docking, and AI tools is now essential for chemists.
- The pharma industry is actively investing in AI, creating high-demand roles globally.
- Transitioning from wet-lab to data-lab skills expands career opportunities significantly.
- Certifications, hands-on projects, and mentorship accelerate employability in this emerging domain.
About Rasayanika
Rasayanika is a premier Chemistry education and training platform, dedicated to equipping students, researchers, and professionals with industry-ready skills in Biotechnology, Cheminformatics, AI/ML, and allied domains. Through expert-led courses, live projects, and placement assistance, Rasayanika bridges the gap between academic knowledge and professional success.
Advance Your Career with AI/ML in Chemistry & Cheminformatics
Take your chemical research skills to the next level with Rasayanika’s AI/ML in Chemistry & Cheminformatics Hands-on Industrial Training Program, starting 28th October 2025. This 30-day online course, with optional 3-, 6-, or 12-month project extensions, offers hands-on experience with DeepChem, RDKit, DiffDock, and AlphaFold, along with guidance on research projects and paper publication. Ideal for students, researchers, and industry professionals, the program equips participants to apply AI/ML to drug discovery, cheminformatics, and materials science, making them industry- and research-ready.
