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
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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-07-01
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| Series: | Clinical and Translational Science |
| Online Access: | https://doi.org/10.1111/cts.13501 |
| _version_ | 1797781695186862080 |
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| author | Monica E. Susilo Chi‐Chung Li Kapil Gadkar Genevive Hernandez Ling‐Yuh Huw Jin Y. Jin Shen Yin Michael C. Wei Saroja Ramanujan Iraj Hosseini |
| author_facet | Monica E. Susilo Chi‐Chung Li Kapil Gadkar Genevive Hernandez Ling‐Yuh Huw Jin Y. Jin Shen Yin Michael C. Wei Saroja Ramanujan Iraj Hosseini |
| author_sort | Monica E. Susilo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T00:00:41Z |
| format | Article |
| id | doaj.art-2bc7d8bf72c444f492e191b7c0cbf612 |
| institution | Directory Open Access Journal |
| issn | 1752-8054 1752-8062 |
| language | English |
| last_indexed | 2024-03-13T00:00:41Z |
| publishDate | 2023-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Science |
| spelling | doaj.art-2bc7d8bf72c444f492e191b7c0cbf6122023-07-13T11:52:35ZengWileyClinical and Translational Science1752-80541752-80622023-07-011671134114810.1111/cts.13501Systems‐based digital twins to help characterize clinical dose–response and propose predictive biomarkers in a Phase I study of bispecific antibody, mosunetuzumab, in NHLMonica E. Susilo0Chi‐Chung Li1Kapil Gadkar2Genevive Hernandez3Ling‐Yuh Huw4Jin Y. Jin5Shen Yin6Michael C. Wei7Saroja Ramanujan8Iraj Hosseini9Genentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAGenentech Inc. South San Francisco California USAAbstract 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.https://doi.org/10.1111/cts.13501 |
| spellingShingle | Monica E. Susilo Chi‐Chung Li Kapil Gadkar Genevive Hernandez Ling‐Yuh Huw Jin Y. Jin Shen Yin Michael C. Wei Saroja Ramanujan Iraj Hosseini 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 Clinical and Translational Science |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| url | https://doi.org/10.1111/cts.13501 |
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