Certara’s Virtual Twin® QSP Models: Transforming Rare Disease Research into Clinical Insights

A Virtual Twin approach is a model-based, data-driven representation of an individual patient’s biological and clinical profile. Using QSP principles, a Virtual Twin model simulates how a specific patient might respond to a treatment by incorporating real-world data such as biomarkers, demographics, and disease progression patterns.

Unlike traditional data-driven “black-box” modeling, Virtual Twin modeling provides a mechanistic, transparent view of how therapies or disease progression impact biology, enabling researchers to predict outcomes and refine treatment strategies with precision.

Global health authorities, including the FDA and EMA, have recognized the value of QSP in supporting model-informed drug development (MIDD). These mechanistic models help strengthen the biological rationale behind clinical trial designs, support dose selection, and inform regulatory submissions, particularly where patient data are limited. These advanced modeling capabilities are powered by Certara IQ™, an AI-assisted QSP modeling software that enables scientists to build, simulate, and share complex QSP and Virtual Twin QSP models with confidence.

In the development of Olipudase alfa (Xenpozyme™) for acid sphingomyelinase deficiency (ASMD), a Virtual Twin modeling approach was used to explore disease similarity between adult and pediatric patients.

By calibrating QSP models with individual patient data, researchers created Virtual Twin models for both adult and pediatric populations. The simulations demonstrated comparable disease mechanisms and treatment responses across age groups, providing key mechanistic evidence to support partial pediatric extrapolation.

The FDA noted that the submitted QSP model offered valuable insights into ASMD progression and response to Olipudase alfa, ultimately contributing to pediatric approval alongside clinical data.

Another example comes from Avalglucosidase alfa (Nexviazyme™) for Pompe disease, a rare lysosomal storage disorder caused by a deficiency of the GAA enzyme.

Sanofi and Certara developed a Pompe QSP model to simulate the disease pathway across different patient groups. Virtual Twin QSP models were generated for both infantile-onset (IOPD) and late-onset (LOPD) Pompe disease patients by adjusting parameters such as residual enzyme activity.

These virtual patients allowed researchers to test and compare treatment responses under different dosing regimens, helping to overcome sample size limitations and disease heterogeneity in clinical development.

The Virtual Twin QSP modeling approach demonstrated how mechanistic modeling can augment clinical evidence, enable better decision-making, and support the use of model-based insights in rare disease programs.

Virtual Twin technology represents a major step forward for model-informed precision medicine. For rare diseases, where every patient counts, Virtual Twin modeling can simulate thousands of personalized outcomes, de-risking clinical trials and accelerating access to therapies. Driving this innovation is Certara IQ, Certara’s QSP modeling software. It empowers teams to translate biological mechanisms into actionable clinical insights, advancing the next generation of Virtual Twin QSP applications

As regulatory agencies continue to embrace model-informed approaches, Virtual Twin modeling is poised to become a cornerstone of modern drug development, bridging the gap between clinical data and patient biology.