Sándor, Szalma

Sándor, Szalma
Institute of Takeda Pharmaceutical Company

Sándor Szalma is senior director of biomedical informatics within the Data Science Institute of Takeda Pharmaceutical Company. Most recently, he was head of Translational Informatics and External Innovation, R&D IT in Janssen Research & Development, LLC. He serves as a member of the industry advisory committee of ELIXIR. Previously, he was member of the board of the Pistoia Alliance, member of the Translational Medicine Advisory Committee of the PhRMA Foundation and led the Data & Knowledge Management Strategic Governance Group of Innovative Medicine Initiative. His past positions included president of MeTa Informatics, general manager of QuantumBio and senior director of Computational Biology and Bioinformatics at Accelrys, Inc. He was co-founder of Acheuron Pharmaceuticals, Inc. He lectured at UCSD Extension and was adjunct professor at Rutgers University in the Computational Biology and Molecular Biophysics program. He is the author of more than 40 scientific publications and book chapters and two patents. He received his doctoral degree in chemistry from A. Szent-Györgyi Medical University in Szeged, Hungary.

He is married to Judit and they have two grown up children Dániel and Dorina. They live in Carlsbad, CA, USA.


Target and biomarker discovery in an open ecosystem

One of the most important characteristics of a successful drug discovery enterprise is to be able to develop a treatment for the right target for the right disease and for right population. An additional aspect is that the developed solution has to be competitive and commercially viable so that the commercial success provides the means for the pharmaceutical enterprise to continue its R&D and commercial operation. The Data Science Institute has been on the forefront of transforming the practice of drug discovery and development within Takeda Pharmaceutical Company. Our R&D leadership is committed to explore ideas in a very open, pre-competitive biomedical ecosystem. By converging external and internal best practices, we strive to renew the pipeline of novel potential treatments for multiple therapeutic areas of focus such as CNS, gastroenterology and oncology. We are championing two main concepts. Sustainable target selection is the first step – we should start by inspecting the heterogeneity of medical practice and patient pathways across target markets and to understand regulatory and market conditions so that the selected targets can be sustained through the arduous road of drug development and regulatory approval. The other concept is to apply a multimodal approach to biomarker discovery so that the right disease and right population can be identified. We are generating deep biomolecular and phenotypic data from patients, harmonize and standardize the practice of data collection and processing and research novel algorithms and methods to extract meaningful information to enable evidence-based decision making. In this talk I will present several use cases describing how we transform the wealth of evidence derived from internal studies, academic collaborations, public-private partnerships and pre-competitive consortia into insights by applying machine learning and advanced analytics and informatics tools.