ArticleClinical and translational science2023
Systems-based digital twins to help characterize clinical dose-response and propose predictive biomarkers in a Phase I study of bispecific antibody, mosunetuzumab, in NHL.
Article in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed, 56 citations in OpenAlex.
- A Novel Step-Up Dosage Regimen for Enhancing the Benefit-to-Risk Ratio of Mosunetuzumab in Relapsed or Refractory Follicular Lymphoma.Clinical pharmacology and therapeutics · 2025Trial
- Quantitative Systems Pharmacology (QSP): Bridging Biology and Mechanism with Clinical Drug Development Decisions.Journal of clinical pharmacology · 2026Review
- Model-Informed Dosing Strategies for Epcoritamab Monotherapy in Relapsed or Refractory Large B-Cell Lymphoma.Clinical pharmacology and therapeutics · 2026Article
- Mechanistic modeling of tumor immune microenvironment reveals strategies to enhance antibody-drug conjugates' efficacy.Journal for immunotherapy of cancer · 2026Article
- AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026Review
- A Review of Virtual Twins in Physiologically-Based Pharmacokinetic Modeling and Simulation.Clinical pharmacology and therapeutics · 2026Review
- Digital twins: a call for an under-developed tool in otolaryngology-head and neck surgery.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Narrative Review of Digital Twins in the Health Domain: Development, Application, and Evidence Consolidation.Medical sciences (Basel, Switzerland) · 2026Review
- Digital twins to accelerate target identification and drug development for immune-mediated disorders.FEBS open bio · 2026Review
- Digital twins of ex vivo human lungs enable accurate and personalized evaluation of therapeutic efficacy.Nature biotechnology · 2026Article
- What Is a Digital Twin in QSP, and Are We Doing It Right?CPT: pharmacometrics & systems pharmacology · 2026Article
- Overview of Quantitative Clinical Pharmacology for T-Cell Engaging Bispecific Antibodies.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Mining the gaps: Deciphering Alzheimer's biology through AI-driven reconciliation.The journal of prevention of Alzheimer's disease · 2025Article
- Leveraging artificial intelligence in antibody-drug conjugate development: from target identification to clinical translation in oncology.NPJ precision oncology · 2025Review
- Clinical modeling of motor function to predict treatment efficacy and enable in silico treatment comparisons in infantile-onset Pompe disease.CPT: pharmacometrics & systems pharmacology · 2025Article
- Integrating artificial intelligence into small molecule development for precision cancer immunomodulation therapy.npj drug discovery · 2025Review
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- Leveraging quantitative systems pharmacology modeling for elranatamab regimen optimization in relapsed or refractory multiple myeloma.NPJ systems biology and applications · 2025Article
- Bispecific Antibodies in Hematologic Malignancies: Attacking the Frontline.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2025Review
- Computational modelling of aggressive B-cell lymphoma.Biochemical Society transactions · 2025Review
Corrections and comments
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Authors and funding
10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Phase I oncology clinical trials often comprise a limited number of patients representing different disease subtypes who are divided into cohorts receiving treatment(s) at different dosing levels and schedules. Here, we leverage a previously developed quantitative systems pharmacology model of the anti-CD20/CD3 T-cell engaging bispecific antibody, mosunetuzumab, to account for different dosing regimens and patient heterogeneity in the phase I study to inform clinical dose/exposure-response relationships and to identify biological determinants of clinical response. We developed a novel workflow to generate digital twins for each patient, which together form a virtual population (VPOP) that represented variability in biological, pharmacological, and tumor-related parameters from the phase I trial. Simulations based on the VPOP predict that an increase in mosunetuzumab exposure increases the proportion of digital twins with at least a 50% reduction in tumor size by day 42. Simulations also predict a left-shift of the exposure-response in patients diagnosed with indolent compared to aggressive non-Hodgkin's lymphoma (NHL) subtype; this increased sensitivity in indolent NHL was attributed to the lower inferred values of tumor proliferation rate and baseline T-cell infiltration in the corresponding digital twins. Notably, the inferred digital twin parameters from clinical responders and nonresponders show that the potential biological difference that can influence response include tumor parameters (tumor size, proliferation rate, and baseline T-cell infiltration) and parameters defining the effect of mosunetuzumab on T-cell activation and B-cell killing. Finally, the model simulations suggest intratumor expansion of pre-existing T-cells, rather than an influx of systemically expanded T-cells, underlies the antitumor activity of mosunetuzumab.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.