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Certara, the leading provider of decision support technology and consulting services for optimizing drug development and improving health outcomes, has announced the launch of Quantitative Systems Pharmacology (QSP) Immunogenicity Consortium.
Modeled after Certara’s highly successful Simcyp Consortium, and believed to be the first of its kind, the QSP Immunogenicity Consortium brings together leading biopharmaceutical companies in a pre-competitive environment to cooperatively develop an Immunogenicity Simulator that will predict immunogenicity of biologics and its impact on their pharmacokinetics, efficacy and safety in diverse patient populations.
Immunogenicity is defined by the US Food and Drug Administration (FDA) as the propensity of the therapeutic protein product to generate immune responses to itself and to related proteins or to induce immunologically-related adverse clinical events. In a recent US FDA review of 121 approved biological products, 89 per cent of them had immunogenicity reported and in 49 per cent of cases it impacted efficacy. Immunogenicity is especially concerning for vulnerable populations with compromised immune systems, often times the exact cohort receiving the biologic treatment.
“Clients rely on Simcyp to research and provide cutting-edge solutions to understand and manage complex physiological drug reactions. Just as sponsors now use mechanistic physiologically-based pharmacokinetic (PBPK) modelling and simulation via the Simcyp Simulator to manage drug-drug interactions (DDIs) and dosing for special populations, they will be able to use these new QSP models to manage immune responses,” said Simcyp President and Managing Director Steve Toon, PhD. “Our models and software tools will enable sponsors to manage immunogenicity by adjusting the biologic dose, route of administration, patient population and/or co-medications. It may also be possible to moderate the immune system’s tolerance of the drug.”
“As immunogenicity to treatment is such a complex process, we need both QSP and mechanistic models of the humoral and cellular responses involved to fully understand it,” said Professor Piet van der Graaf, PharmD, PhD, vice president and head of Certara QSP. “Current immunogenicity modelling uses machine learning to predict immunogenicity directly from the biologic drug’s genetic sequence. This is insufficient because it doesn’t account for the full complexity and dynamics of potential physiological responses or the differences between patient populations.”
“We will use a variety of structural, in vitro and in vivo input parameters for our dynamic models, which will be implemented in a robust IT platform coupled to a virtual patient simulator that can be used to make development and regulatory decisions,” added Professor van der Graaf.
