Project Optimus, an FDA initiative: Considerations for cancer drug development internationally, from an academic perspective

Frontiers in Oncology, Journal Year: 2023, Volume and Issue: 13

Published: March 3, 2023

Modern cancer therapeutics are increasingly targeted, bringing the promise of new and improved activity, alongside better tolerability. However, while many indeed resulting in dramatic improvements disease control patient survival, short- long-term tolerability has not always accompanied it. The choice dose schedule is often upper range therapeutic window, driven by maximum tolerated (MTD) model previous cytotoxic agents. There increasing recognition that this needs to change, taking a more holistic approach determine optimal for desired biological effects early clinical development. In US, FDA's Oncology Centre Excellence addressing via Project Optimus initiative: aiming reform optimisation studies so they can demonstrate most appropriate selection. Early development will need dose-exposure, -pharmacodynamic, -toxicity -activity relationships, including randomised evaluations Regulatory agencies outside US similarly exploring this. Along with Australia, Brazil, Canada, Israel, Singapore Switzerland, UK participates Orbis, collaborative program FDA accelerate access medicines through coordinated regulatory review. Close alignment be important internationally require changes across industry, academic units small biotech. We discuss our perspective on implications, opportunities, phase oncology trials as uniquely charity-funded drug facility, Drug Development within Cancer Research charity.

Language: Английский

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Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development

CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 13(5), P. 691 - 709

Published: Nov. 16, 2023

Project Optimus is a US Food and Drug Administration Oncology Center of Excellence initiative aimed at reforming the dose selection optimization paradigm in oncology drug development. This project seeks to bring together pharmaceutical companies, international regulatory agencies, academic institutions, patient advocates, other stakeholders. Although there much promise this initiative, are several challenges that need be addressed, including multidimensionality problem oncology, heterogeneity cancer patients, importance evaluating long-term tolerability beyond dose-limiting toxicities, lack reliable biomarkers for efficacy. Through lens Totality Evidence with mindset model-informed development, we offer insights into by building quantitative knowledge base integrating diverse sources data leveraging modeling tools build evidence dosage considering exposure, disease biology, efficacy, toxicity, factors. We believe rational can achieved improving outcomes maximizing therapeutic benefit while minimizing toxicity.

Language: Английский

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An industry perspective on current QSP trends in drug development

Journal of Pharmacokinetics and Pharmacodynamics, Journal Year: 2024, Volume and Issue: unknown

Published: March 5, 2024

2023 marks the 10th anniversary of Natpara's submission to US FDA, which led first recorded regulatory interaction where a decision was supported by Quantitative and Systems Pharmacology (QSP) simulations. It had taken about 5 years for timid QSP discipline emerge as an effective Model-Informed Drug Development (MIDD) tool with visible impact in pharmaceutical industry. Since then, presence environment has continued increase, point that Agency reported 60 submissions 2020 alone, representing ~ 4% their annual IND [1]. What sort industry mindset enabled reach this level success? How does fit within MIDD paradigm? Does mean same Discovery Clinical projects? do 'platforms' compare 'fit-for-purpose' models industrial setting? Can empirical Pharmacokinetic-Pharmacodynamic (PKPD) modelling be complementary? validation is required inform drug development decisions? This article reflects on all these questions, particular addressing those audiences limited line-of-sight into decision-making machinery.

Language: Английский

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Dose Optimization in Oncology Drug Development: An International Consortium for Innovation and Quality in Pharmaceutical Development White Paper

Clinical Pharmacology & Therapeutics, Journal Year: 2024, Volume and Issue: 116(3), P. 531 - 545

Published: May 16, 2024

The landscape of oncology drug development has witnessed remarkable advancements over the last few decades, significantly improving clinical outcomes and quality life for patients with cancer. Project Optimus, introduced by U.S. Food Drug Administration, stands as a groundbreaking endeavor to reform dose selection drugs, presenting both opportunities challenges field. To address complex optimization challenges, an Oncology Dose Optimization IQ Working Group was created characterize current practices, provide recommendations improvement, develop toolkit, engage Health Authorities. Historically, cytotoxic chemotherapeutics focused on maximum tolerated dose, paradigm that is less relevant targeted therapies new treatment modalities. A survey conducted this group gathered insights from member companies regarding industry practices in optimization. Given effort multidimensional high failure rates due lack clinically efficacy, advocates case‐by‐case approach inform timing, specific quantitative targets, strategies optimization, depending factors such disease characteristics, patient population, mechanism action, including associated resistance mechanisms, therapeutic index. This white paper highlights evolving nature impact need tailored evidence‐based optimize dosing regimens effectively.

Language: Английский

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Stronger together: a cross-SIG perspective on improving drug development

Journal of Pharmacokinetics and Pharmacodynamics, Journal Year: 2025, Volume and Issue: 52(1)

Published: Jan. 17, 2025

Language: Английский

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From Prospective Evaluation to Practice: Model-Informed Dose Optimization in Oncology

Drugs, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

One dose does not fit all, especially in oncolytic drugs, where side effects and therapy failures highlight the need for personalized dosing approaches. In recent years, quest to apply model-informed precision oncology drugs has gained significant momentum, reflecting its potential revolutionize patient care by tailoring treatments individual pharmacokinetic profiles. Despite this progress, (yet) become widely integrated into routine clinical care. We aimed explain from a viewpoint while addressing all prospective implementation validation studies field of oncology. identified 16 different which validation/implementation been performed. Although these are mostly focused on attaining adequate drug exposures reducing inter-individual variability, improved outcomes after performing were shown busulfan, high-dose methotrexate. Toxicities significantly reduced busulfan cyclophosphamide treatment. contrast, carboplatin, used Calvert formula, no was deemed necessary as therapeutic window had extensively validated. Model-informed be added value is expected change regimens future.

Language: Английский

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Moving the needle for oncology dose optimization: A call for action

CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2024, Volume and Issue: 13(6), P. 909 - 918

Published: May 22, 2024

Project Optimus is a major FDA initiative aimed at ensuring dose optimization in oncology drug development, moving away from the maximum tolerated paradigm and prospectively characterizing dose–response for efficacy safety patient-focused maximization of benefit versus risk.1-3 Mitigating toxicities enhancing overall risk therapies necessitates with commitment to evaluation innovative dosing paradigms including individualized approaches, where appropriate. This requires quantitative integration pharmacological mechanism action, efficacy, context associated population variability. The problem cancer pathophysiology, variability sits neatly intersection translational/ precision medicine clinical pharmacology important approach mindset. Forums convened on topic largely engage scientific leaders primarily working research medicine. These include workshops organized by Friends Cancer Research (FOCR),4 American Society Clinical Oncology (ASCO),5, 6 Association (AACR),7, 8 International Pharmacometrics (ISoP)9 partnership US Food Drugs Administration (FDA). Of note, some these efforts have yielded seminal publications1, 2, 10-13 White Papers14 offering initial recommendations, availability Draft guidance topic.15 We posited that Pharmacology Therapeutics (ASCPT) – as premier professional organization translational optimally positioned host discussion opportunities our constituent disciplines (e.g., science, pharmacology, pharmacometrics) synergistically address this multi-disciplinary approach. To end, session was 2023 ASCPT Annual Meeting bringing together representative three journals (CPT), Translational Science (CTS), CPT: Systems (PSP). leaders, at-large representatives medicine, were invited bring forward their opinions participate fireside chat identify needle. enabled engagement broad group experts without requiring primary or affiliation therapeutic area, thereby maximizing diversity opinion, out-of-the-box solutioning, fresh perspectives should help advance us beyond current state. Ahead Meeting, survey launched members meeting attendees get finger pulse Society's membership issues faced provide substrate expert panel. Herein, we present findings survey, review insights gained recommendations communities join forces drive progress. A focused developed sent out February broader session, which consisted six questions relevant (Data S1). open 3 weeks 65 respondents participated survey. not only interested understanding background may influence feedback, but also various approaches challenges modalities. In response question about full time R&D, 58% either engaged had part R&D. suggested feedback diverse backgrounds, intended. Similarly, if strategies other areas are therapies. 86% indeed oncology. Three applied one utility pharmacodynamic (PD) biomarkers, another selection finally study designs focus randomization. 92% responses suggest PD biomarkers least useful. Exposure-response modeling (57%) followed pharmacokinetic (PK)/PD (28%) most preferred selecting doses. 62% did consider randomized dose-ranging necessary optimization, suggesting value application case-by-case leveraging totality evidence optimize (Figure 1). Given area wide range modalities small molecules cell therapies, sought understand level challenge developing each Respondents noted next-generation cytotoxic agents, molecule targeted monoclonal antibodies relatively straightforward many historical examples guide selection. However, antibody-drug conjugates viewed be moderately complex while newer such multi-specific biologics considered very challenging few no 2). From perspective, find right patients swiftly safely possible, buttressed nonclinical data. doesn't always complex. Goldstein et al.16 describe simple concept agents first-in-human setting. suggestions can implemented today. approved doses 25 examined average free concentration steady state (Css) determined similar vitro potency (half-maximal inhibitory (IC50)). Furthermore, authors propose revised trial design therapy cohort expansion initiated less than when there activity Css exceeds threshold informed potency. Ji al.17 case, an inhibitor Porcupine, membrane-bound O-acyltransferase required Wnt secretion. pathway expressed skin tissues; AXIN2 mRNA expression robust sensitive biomarker pathway. predominant issue case dysgeusia. performed integrated PK exposure-response analyses data determine recommended expansion, rather conventional More possible great utility, particularly Weddell al.18 elegant mechanistic model characterizes antibody conjugate (ADC) pharmacokinetics tumor penetration incorporating growth inhibition via ADC binding radially across solid tumors. demonstrates low target expression, payload increased. mechanistically links rates relapse resistance could facilitate optimization. recent example, Susilo al. leveraged systems (QSP) anti-CD20/CD3 T-cell engaging bispecific antibody, mosunetuzumab, account different regimens inter-patient heterogeneity phase I biological determinants dose/exposure-response relationships using novel QSP-derived digital twins approach.19 Approaches nature raise multi-dimensional dimensions dose, patient population, combination partner routinely development. new, development continuing realized. Recent indicate emerging circulating DNA (ctDNA).20, 21 ctDNA, found bloodstream, manifold, detecting diagnosing cancer, guiding tumor-specific treatment, monitoring treatment remission. underlying relationship on-treatment ctDNA dynamics inform definition clinically active represents untapped opportunity. Another innovation has been health technologies proposed multi-domain, capturing functional status, health-related quality life oncology,22 realize promise dosage improved during long-term therapy. ASCPT, pharmacologists, scientists key role collaboration stakeholders. straddles variety stakeholders academics, industry, regulators, others brainstorming consensus formation. For al.,23 reported annual symposium. number observed before Optimus, post-market dose-finding, continued use traditional + designs, lack characterization chronic toxicity, adopting testing more 2/3 trials. fields science yet value-added Cross-stakeholder work expected field increased biomarker-based model-informed solutions finding paper "The Future Trial Design Oncology," Spreafico co-workers Toronto Princess Margaret Centre24 how discovery shifted chemotherapy histology-based targets molecularly immune subsets stratified diagnostic tools. argue classical urgently needs transformed ensure will revolution timely manner. wide-ranging call they patient-centric framework trials, maps journey participant dynamic adaptive continuously technological innovations develop strategies. They conclude success trials based fundamental principles acting locally learn globally treating participants individually collectively." speaks directly opportunity play core new paradigm, particular regard individualization quantitative, integrate knowledge drug, disease, patient. An example QSP, conducted ISoP identified tool utilized developers regimen optimization.25 presented Li al.,26 who II (R2P2D) epcoritamab, CD3×CD20 (bsAb). justified approach, preclinical, PK, biomarker, tumor, dose-escalation I/II trial, basis methods adequately predict bsAbs. Therefore, trimer formation predicted instead actual measures used prediction. Along same lines, Chelliah consortium pharmaceutical companies,27 made conventional, empirical pharmacometrics do fully capitalize all available disease QSP models rational better alternative IO Their proposal "virtual patients" simulated under conditions mimic added aligned earlier-mentioned call-to-action outlined Figure 2 publication,24 future already arrived. Poorly characterized schedule lead provides toxicity additional severe require high rate reductions premature discontinuation result missed drug. remain significant model-based sometimes involve non-static posology, outcome-based adaptation risk.28, 29 offers pivotal reform framework.2, 3, 14, 30-33 By integrating lifecycle, Bayesian learning-and-confirming mindset spectrum, lifecycle 3; top panel) consists building revising collection answer define label. priori consideration pharmacologic inputs elements establishing early access points within open-label design. components improve efficiency enable rapid updates emerge end-to-end utilizes it generated.34-36 predict, interpret, contextualize data, even through simulations outcomes, approximate real-time analysis. both influenced by, influential studies, becomes hypothesis lifecycle. Contemporary evolved utilize model-assisted designs. offer seamless movement cohorts blend escalation evaluation.37, 38 Introducing metrics like pharmacodynamics lower underdosing intrinsic extrinsic factors explain inter-individual reduce bias determination. Several extend dose-toxicity exposure benefit–risk potential drug.39-44 mindset, well-established remains under-utilized It uses program confirm generated.36 (bottom illustrates framework. Expanded larger (to overcome sample size biology impact ability establish signals efficacy) generate preliminarily characterize between exposure, toxicity/tolerability, efficacy. subsequent trial. combined prior collectively defining distributions being informative source quality. probability distribution collected posterior levels desired ratio. When quantity generated high, highly later possibly reducing duration so effective become faster. Maximizing frameworks depend inter-disciplinary alliances pharmacologists statisticians,45 exchange ideas lessons industry regulatory agencies.5 harmonized learnings collaborative interactions further acceptance set precedent programs, ultimately realizing methodologies One main advantages examining non-oncologist translate successful aid enriching holistic toward solving longstanding problems. clear correlate HIV discovery. 1980s, expectancy following AIDS diagnosis approximately year. And 1990s, leading cause death among Americans aged 44. ways, much urgency save lives need therapeutics control epidemic fueled beginning unsophisticated zidovudine initially studied 200 mg q4h, caused anemia neutropenia. fine-tuning eventually led its 300 twice daily. advancements along way infection regarded condition near normal life. Some included deeper continual mechanisms antiretroviral enhanced diagnostics, biomarkers. deployed simultaneously, integrated, advanced methodology urgent public problem. biggest faces now operationalize. No matter proper prospective dose-finding outset, focusing strategy, incredibly beneficial. examples, blood pressure reduction, lowering HbA1c, reduction LDL cholesterol extensively correlated strongly outcomes interest surrogate endpoints. exploration stage critical investment return. R&D explosive advances Drug involves Dose several 4), demanding inter-connected iterative generation Totality Evidence approaching tailored medicines cancers molecular footprints, cannot approached Size Fits Diversity profile immunophenotype considerations patients. Advances sciences informatics enabling deep immunology populations, rapidly applications machine learning artificial intelligence harness multimodal multidimensional represent invaluable platforms requirements. Such elevate fidelity selection, As evident results obligate requirement cases 60% respondents. Indeed, exist integrative confidence anticancer published stories.26, 46-48 substantiated consistency multiple sources mechanism-informed manner simulation.49 critically challenging. pleased note progress publications highlighting translational, therapeutics.50-55 real-life continue refine best practices invite readership cross-sector practitioners submit publication. trust rigorous debate ensue practice, facilitated ASCPT's Networks Communities, go long elevating benefit/ Editorial support provided Dr. Madhuri Shendre, BAMS (Merck Specialties Pvt. Ltd., Bengaluru, India, affiliate Merck KGaA). funding received work. declared competing interests Data S1. Please note: publisher responsible content functionality any supporting information supplied authors. Any queries (other missing content) directed corresponding author article.

Language: Английский

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Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Journal of Pharmacokinetics and Pharmacodynamics, Journal Year: 2024, Volume and Issue: 51(6), P. 581 - 604

Published: June 21, 2024

Language: Английский

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Response‐Based Dosing for Ponatinib: Model‐Based Analyses of the Dose‐Ranging OPTIC Study

Clinical Pharmacology & Therapeutics, Journal Year: 2023, Volume and Issue: 114(2), P. 413 - 422

Published: May 23, 2023

Optimizing Ponatinib Treatment in CP-CML (OPTIC) was a randomized, phase II dose-optimization trial of ponatinib chronic phase-chronic myeloid leukemia (CP-CML) resistant to ≥ 2 tyrosine kinase inhibitors or with T315I mutation. Patients were randomized starting doses 45-, 30-, 15-mg once daily. receiving 45- 30-mg reduced upon achievement ≤ 1% BCR::ABL1IS (≥ molecular response 2-log reduction (MR2)). The exposure-molecular relationship described using four-state, discrete-time Markov model. Time-to-event models used characterize the between exposure and arterial occlusive events (AOEs), grade 3 neutropenia, thrombocytopenia. Increasing systemic exposures associated increasing probability transitioning from no MR1, MR1 odds ratios 1.63 (95% confidence interval (CI), 1.06-2.73) 2.05 CI, 1.53-2.89) for dose increase, respectively. significant predictor AOEs (hazard ratio (HR) 2.05, 95% 1.43-2.93, increase). In exposure-safety neutropenia thrombocytopenia, thrombocytopenia (HR 1.31, 1.05-1.64, Model-based simulations predicted clinically meaningful higher rate MR2 at 12 months 45-mg (40.4%) vs. (34%) (25.2%). exposure-response analyses supported 45 mg 15 patients CP-CML.

Language: Английский

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A multistate modeling and simulation framework to learn dose–response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer

CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 12(11), P. 1738 - 1750

Published: May 11, 2023

The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions transition times from enrollment progression, death, evaluating transition-specific dose effects. This study aims apply the multistate pharmacometric modeling simulation framework in a optimization setting of bintrafusp alfa, fusion protein targeting TGF-β PD-L1. A model with six states (stable disease [SD], unknown, dropout, death) was developed describe totality endpoints data (time PFS, OS) 80 patients non-small cell lung cancer receiving 500 or 1200 mg alfa. Besides dose, evaluated predictor include time, demographics, premedication, factors, individual clearance derived pharmacokinetic model, tumor dynamic metrics observed size model. We found that probabilities progression death upon decreased over time since enrollment. Patients metastasis at baseline had higher probability progress than without had. Despite failed be statistically significant any transition, combined effect quantified through dose-specific estimates still informative. Simulations predicted 69.2% least 1 month longer, and, 55.6% 2-months longer median OS compared supporting selection future studies.

Language: Английский

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