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2026 年 4 月 28 日

After four years, QSPC 2026 in Leiden brought the quantitative systems pharmacology community back together, and it felt like a milestone moment for the field. With close to 300 attendees, a packed scientific program, and three days of discussions spanning quantitative systems pharmacology (QSP), physiologically based pharmacokinetic (PBPK) modeling, AI/ML, and translational pharmacology, the conference highlighted just how far the discipline has come, and where it’s headed next.

More than the science: Community, conversations, and Leiden

Beyond the sessions, QSPC continues to stand out for its community-driven atmosphere.

Leiden provided the perfect setting:

  • Beautiful spring weather that kept energy high
  • Coffee-fueled discussions between sessions
  • Walkable city moments that extended conversations beyond the venue

With a relatively intimate size, the meeting made it easy to:

  • Reconnect with long-time collaborators
  • Meet new partners across academia, biotech, and pharma
  • Have deeper, more meaningful scientific discussions

The panels were a particular highlight, creating space for open dialogue around:

  • The growing role of QSP in regulatory submissions
  • The need for credibility frameworks and standardization
  • How to move from promising applications to routine use in decision-making

Highlights from key talks

New modalities bring new modeling challenges

Work on oncolytic viruses (OVs) showcased how QSP is expanding into increasingly complex therapeutic areas.

Key takeaways:

  • OVs operate through dual mechanisms: direct tumor killing and immune activation
  • Despite decades of research, only a handful of therapies are approved, with most still in early-phase trials
  • Major challenges remain:
    • Translating preclinical findings to humans
    • Identifying predictive biomarkers
    • Optimizing delivery routes

The takeaway: mechanistic understanding is still evolving, and QSP is essential to unlocking these therapies

Virtual patients are driving real decisions

A consistent theme across multiple talks was the rise of virtual patients and in silico trials.

Britta Wagenhuber’s work demonstrated how integrating clinical and preclinical data, omics datasets, and disease biology and pharmacology, can enable simulations that:

  • Accelerate development timelines
  • Support candidate selection
  • Predict outcomes in subpopulations

In one case, this approach helped accelerate a program by ~1 year. QSP is no longer just explanatory. It’s becoming decision-enabling.

QSP in regulatory submissions is a reality

One of the clearest signals of maturity came from talks focused on regulatory applications.

Work presented by Takeda showed how:

  • QSP models calibrated with combined datasets
  • Underwent additional external validation
  • Were used to simulate virtual clinical trials

In this case, regulators accepted the modeling as confirmatory evidence in an ultra-rare disease setting.

More broadly:

  • Regulators are increasingly open to QSP
  • There is growing emphasis on how models are validated and communicated

This marks a shift toward QSP as a trusted component of regulatory strategy.

From variability to individualization

Several talks focused on understanding patient variability and moving toward individualized care.

Elke’s work on obesity and drug clearance highlighted that:

  • Clearance changes systematically with obesity, but not uniformly
  • Effects depend strongly on drug properties and disease state
  • Simple scaling approaches introduce significant error

The key message: Dosing cannot be formula-based. It must be individualized using mechanistic insight.

Certara posters took the stage

Beyond the main sessions, the poster presentations at QSPC 2026 offered a closer look at cutting-edge applications of QSP and PBPK modeling. Certara’s contributions, in particular, showcased how mechanistic modeling is being applied across modalities, from biologics to cell therapies.

1. Advancing Ocular Drug Modeling for Anti-VEGF Therapies

Minimal PBPK model with detailed ocular physiology to compare target occupancy for anti-VEGF antibodies
Presenter: Suruchi Bakshi (with Merck)

This work introduced a streamlined PBPK model incorporating detailed ocular physiology to evaluate target engagement across anti-VEGF therapies.

Why it stands out:

  • Enables comparison of antibody performance in the eye
  • Supports optimization of dosing and delivery strategies
  • Addresses a critical need in ophthalmology drug development

2. Understanding T-Cell Exhaustion in Immunotherapy Relapse

QSP modeling of T-cell exhaustion as a driver of relapse in long-term treatment with T-cell engagers
Presenter: Jonas Denk

This QSP model explores how T-cell exhaustion contributes to relapse, a major challenge in immuno-oncology.

Key contributions:

  • Mechanistic insight into long-term treatment dynamics
  • Identification of relapse drivers
  • Potential strategies to improve durability of response

3. IO Simulator: A Platform for Immuno-Oncology Drug Development

IO Simulator: A QSP platform for immuno-oncology (IO)
Presenter: Sirin Yonucu

This platform represents a move toward scalable, reusable QSP frameworks for IO.

What it enables:

  • Simulation of complex tumor–immune interactions
  • Evaluation of combination therapies
  • Faster hypothesis testing across drug candidates

4. Translating pH-Dependent FcRn Binder PK/PD Across Species

Minimal PBPK model for pH-dependent FcRn binders with optional albumin binding domain
Presenter: James Wade

This model addresses the complexity of pH-dependent binding on FcRn-mediated recycling and IgG levels.

Highlights:

  • Cross-species translation (mouse → monkey → human)
  • Flexible modeling that can include albumin-binding domains
  • Improved prediction of PK/PD behavior

5. Model-Informed First-in-Human Dose Selection for CAR-T Therapy

Model-informed first-in-human dose selection for BCMA CAR-T therapy in multiple myeloma
Presenter: Chris Morris

This work demonstrates how modeling can support safer and more efficient clinical entry for cell therapies.

Impact:

  • Reduces uncertainty in dose selection
  • Supports regulatory strategy
  • Enhances early-stage decision-making

6. Mechanistic Modeling to Optimize CAR-T Therapy Outcomes

Mechanistic modeling of CAR-T therapy in multiple myeloma
Presenter: Vicky Kostiou

This model integrates public and real-world data to better understand patient response.

Key insights:

  • Identification of patient-specific response drivers
  • Evaluation of multi-antigen targeting strategies
  • Support for personalized treatment approaches

7. Modeling Hematopoiesis to Advance MDS and AML Therapies

A QSP Platform Model of Hematopoiesis for Evaluating Therapeutic Interventions in MDS and AML
Presenter: Viji Chelliah

This poster introduces a QSP platform model of hematopoiesis designed to support drug development in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), two areas with complex disease biology and significant unmet need.

Key highlights:

  • Captured the dynamics of blood cell formation and disruption in disease
  • Enabled evaluation of therapeutic interventions across multiple mechanisms
  • Supported translation from biology to clinical outcomes in hematologic disorders

8. [Client poster] Model-Based Patient Selection and Dosing Strategies for HRAS and PIK3CA dysregulated HNSCC: A QSP Model for Alpelisib and Tipifarnib Combination

Authors: Jaehee Shim1, Douglas Chung1, Alison Smith2, Shivani Malik2, Binaifer Balsara2, Francis Burrows2, Piet H. van der Graaf1,3,4, Amitava Mitra2*
1. Certara Applied BioSimulation, Sheffield, UK, 2. Kura Oncology, Inc., San Diego, CA, USA, 3. Leiden Academic Centre for Drug Research, Leiden University, The Netherlands, 4. Cincinnati Children’s Hospital Medical Center, US. *Presenting Author

This poster presents a mechanistic QSP model of PI3K and HRAS signaling to guide patient selection and dosing for combination therapy in head and neck cancer, integrating preclinical, clinical, and molecular data into a unified framework.

Highlights:

  • Predicts tumor response across genetically defined patient subgroups, identifying those most likely to benefit
  • Uses virtual patient simulations to optimize dosing and improve therapeutic outcomes
  • Shows that treatment response varies significantly by mutation type, reinforcing precision medicine strategies

9. [Client poster] A Quantitative Systems Pharmacology Model of Type 1 Diabetes Progression to Support Immunomodulatory Drug Development

Authors: E. Roesch (1), R. Sheehan (2), G. Boka (1), V. Chelliah (2), M. Jansen (2), M. Kumar (1), M. Peakman (1), E. Sundermann (1), P. van der Graaf (2), B. Wagenhuber (1)
1. Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany, 2. Certara, Radnor, US.

This poster presents a quantitative systems pharmacology (QSP) model of Type 1 Diabetes (T1D) progression that integrates autoimmune mechanisms with metabolic outcomes across defined disease stages. The model provides a mechanistic framework to support immunomodulatory drug development by linking immune-mediated β‑cell destruction to clinically relevant glycemic endpoints, both in the presence and absence of exogenous insulin therapy.

Key highlights:

  • Mechanistically captured the islet–immune cycle driving autoimmune β‑cell loss and natural disease progression
  • Linked immune activity and β‑cell preservation to clinical and metabolic outcomes such as HbA1c, C‑peptide, and time‑in‑range
  • Forms a mechanistic framework for quantitatively evaluating immunomodulatory treatments and disease‑modifying effects

10. [Client poster] Can FcRn-inhibitors be improved by adding an albumin-binder? A case study of how to influence molecule design at concept phase with M&S

Authors: Katharina Koep1, James Wade2, Athena Grant2, Allison Christiaansen3, Achim Doerner1, Anis Krache1, Enrico Guarnera1, Tom Snowden2, Piet van der Graaf2
1. Merck KGaA, Darmstadt, Germany, 2. Certara UK Limited, London, England, 3. EMD Serono

This work shows how a minimal PBPK model can be used at the concept stage to evaluate design hypotheses, specifically whether adding an albumin-binding domain could improve FcRn inhibitors, before any molecule is physically created.

Highlights:

  • Albumin binding extends half-life and improves PK, but not enough to enable practical subcutaneous dosing
  • Modeling enables early go/no-go decisions, reducing reliance on costly experimental iteration
  • Highlights limitations of animal models due to species differences in FcRn and albumin binding

Certara IQ™ takes the stage: Live demos

While scientific talks and posters showcased the evolution of QSP, Certara IQ™ demos, led by Andrew Matteson, emerged as a standout highlight. Attendees weren’t just seeing what’s possible; they were able to see how it actually works in practice.

From Models to Usable Workflows

The demos focused on how Certara IQ enables teams to:

  • Integrate diverse datasets into a unified modeling environment
  • Streamline QSP and PBPK workflows
  • Improve collaboration across multidisciplinary teams
  • Accelerate decision-making with more accessible, scalable tools

Key trends across QSPC 2026

Across sessions, several consistent themes emerged:

  1. Convergence of QSP and PBPK: PBPK had a stronger presence than expected, signaling increasing integration between disciplines.
  2. Virtual Populations Everywhere: Virtual patients are now central to trial simulation, variability analysis, decision-making, though questions remain around how they are generated and validated.
  3. Regulatory Engagement Is Increasing: There is growing alignment on the role of QSP in submissions, the need for credibility frameworks, and best practices for model reporting.
  4. AI/ML Is Emerging, But Still Maturing: AI is being explored for model building, automation workflows, and data integration. But compelling, large-scale success stories are still developing.
  5. Expansion into New Modalities: From mRNA therapeutics, gene therapies, oncolytic viruses, QSP is being pushed into areas where traditional approaches struggle.
  6. Speed and Scalability Are Becoming Critical: There is increasing demand for faster decision-making, reusable platform models, and more scalable modeling workflows.

Looking ahead: QSPC 2030

Because QSPC happens only every four years, it offers a unique opportunity to reflect on progress.

By the next meeting, we may see:

  • Routine use of QSP in regulatory submissions
  • Standardized approaches to model validation and credibility
  • Broader adoption of virtual trials in development programs
  • Deeper integration of AI with mechanistic models
  • Increased use of QSP in clinical decision-making

Most importantly, the field is aligning around a shared goal: Turning models into measurable impact for patients. No longer a niche capability, QSP is becoming central to how we understand, develop, and deliver therapies.

Author

Jessica Sinha

Associate Director, Marketing – QSP, Certara

Jessica Sinha is an accomplished marketing leader with more than eight years of experience spanning B2B, brand, content, and digital marketing in the life sciences sector. At Certara, she leads strategic marketing initiatives for Quantitative Systems Pharmacology (QSP), combining her scientific foundation in bioengineering with a passion for clear, impactful communication.

This summary was built with significant contributions from Certara’s QSP team in attendance at QSPC 2026.

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常见问题解答

What is QSPC?

QSPC (Quantitative Systems Pharmacology Conference) is a global scientific meeting focused on advancing quantitative systems pharmacology (QSP), bringing together experts from pharma, biotech, academia, and regulatory agencies. QSPC is held every four years, making it a key milestone event for tracking long-term progress and trends in the field.

Who attends QSPC?

Attendees include:

  • QSP scientists and pharmacometricians
  • Drug development leaders in pharma and biotech
  • Academic researchers
  • Regulatory experts

What topics are covered at QSPC?

The conference typically spans:

  • QSP and PBPK modeling
  • 模型引导的药物开发(MIDD)
  • AI/ML in MIDD approaches

Why is QSPC important for drug development?

QSPC highlights how modeling approaches are evolving from research tools into decision-making frameworks, with growing impact on regulatory submissions and clinical strategy.

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