HomeWebinarsFormulation and Predictive Technologies to De-Risk Solid-State Variation in Drug Development

Formulation and Predictive Technologies to De-Risk Solid-State Variation in Drug Development


This webinar will present the concepts of crystal structure and polymorphism in drug development of oral solid dosage forms, will introduce CSP as an option to minimize solid-state risks, and, finally, will describe how mesoporous silica can be used as a last-resort technology to homogenize a solid form from exhibiting polymorphism. All of the above will be supported by a range of case studies from a diverse and highly relevant chemical space. Finally, we will propose an integrated workflow to combine computational and formulation technologies to optimize the development of orally delivered small molecules.

In this webinar, you will learn:

  • The Importance of solid form in the development of orally delivered dosage forms
  • How Crystal Structure Prediction (CSP) can be used to optimize solid form and identify challenging molecules
  • Why mesoporous silica is an attractive formulation technology to homogenize particle properties
  • About the combination of predictive and formulation technologies as a platform approach to solid formulation development


Gudrun Birk, Ph.D.

Gudrun Birk, Ph.D.


Head of Controlled Release

Gudrun is a pharmacist by education and has been with MilliporeSigma since April 2014. Within the R&D organization, she and her team focus on the development of innovative new excipients and functional excipients systems for solid oral dosage forms. She presents research results at scientific conferences and in publications as well as provides customers with guidance and support for their unique formulation challenges. Gudrun studied pharmacy at the University of Freiburg, Germany, and holds a Ph.D. from Ludwig Maximilian University of Munich, Germany.

Michael Belucci

Michael Belucci


Senior Director - Solid Form Design

Dr. Michael Bellucci is a senior director at XtalPi, Inc. where he leads a research team that develops algorithm technologies for solid form development and risk assessment as well as drug discovery. Prior to his current role, he was a research scientist at MIT in the Novartis-MIT Center for Continuous Manufacturing where he led many research projects in collaboration with pharmaceutical companies. His solid-state research has focused on combining computational chemistry and A.I./machine learning methods to study processes and properties associated with molecular crystals, such as solubility, morphology, surface adsorption, polymorphic transitions, and nucleation and crystallization.  Michael is a theoretical and computational chemist by education and holds a Ph.D. in chemistry from Boston University.

Webinar Information

Pharma and biopharma manufacturing

  • Solid Formulation Strategies
  • Duration:1h

  • Language:English

  • Session 1:presented November 15, 2022

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