Modelling and Process Analytical Technology (PAT) Tools for Monitoring, Control, and Impurity Profiling for Continuous Synthesis Platform of a Model Drug Substance
Symposium: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 1
Symposium: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 1
Symposium: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 2
Symposium: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 2
Keynote: Using AI/ML What is Lacking to Make AI/ML Really Successful in the Drug Discovery/Development Processes
Keynote Speaker: Aleksander Mendyk, MSc, PhD, DSc, Professor – Chair and Department of Pharmaceutical Technology and Biopharmacutics, Faculty of Pharmacy, Jagiellonian University - Medical College
Keynote: Using AI/ML What is Lacking to Make AI/ML Really Successful in the Drug Discovery/Development Processes
Location: 251 ABC, Salt Palace Convention Center
Keynote Speaker: Aleksander Mendyk, MSc, PhD, DSc, Professor – Chair and Department of Pharmaceutical Technology and Biopharmacutics, Faculty of Pharmacy, Jagiellonian University - Medical College
Speaker Spotlight: A Slice of the Immunerdy Pecan Pie- Regulatory Stakeholders in CDER’s Integrative Immunogenicity Review of Therapeutic Proteins and Peptides
Speaker Spotlight: A Slice of the Immunerdy Pecan Pie- Regulatory Stakeholders in CDER’s Integrative Immunogenicity Review of Therapeutic Proteins and Peptides
Location: Spotlight Stage A, Aisle 1100, Exhibit Hall
Rapid Fires: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 1
Rapid Fires: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 1
Rapid Fires: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 2
Rapid Fires: Making Data Work for Us – Applying and Combining Empirical (AI/ML) and Mechanistic Modeling in the Preclinical, Clinical, and Post-Approval Realms 2
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