Challenges and Opportunities in Dose Finding in Oncology and Immuno-oncology

Integrated modeling of biomarkers, survival and safety in clinical oncology drug development

Model-based approaches, including population pharmacokinetic-pharmacodynamic modeling, have become an essential component in the clinical phases of oncology drug development. Over the past two decades, models have evolved to describe the temporal dynamics of biomarkers and tumor size, treatment-related adverse events, and their links to survival. Integrated models, defined here as models that incorporate at least two pharmacodynamic/ outcome variables, are applied to answer drug development questions through simulations, e.g., to support the exploration of alternative dosing strategies and study designs in subgroups of patients or other tumor indications. It is expected that these pharmacometric approaches will be expanded as regulatory authorities place further emphasis on early and individualized dosage optimization and inclusive patient-focused development strategies. This review provides an overview of integrated models in the literature, examples of the considerations that need to be made when applying these advanced pharmacometric approaches, and an outlook on the expected further expansion of model-informed drug development of anticancer drugs.

A Bayesian Dynamic Model-Based Adaptive Design for Oncology Dose Optimization in Phase I/II Clinical Trials

With the development of targeted therapy, immunotherapy, and antibody-drug conjugates (ADCs), there is growing concern over the "more is better" paradigm developed decades ago for chemotherapy, prompting the US Food and Drug Administration (FDA) to initiate Project Optimus to reform dose optimization and selection in oncology drug development. For early-phase oncology trials, given the high variability from sparse data and the rigidity of parametric model specifications, we use Bayesian dynamic models to borrow information across doses with only vague order constraints. Our proposed adaptive design simultaneously incorporates toxicity and efficacy outcomes to select the optimal dose (OD) in Phase I/II clinical trials, utilizing Bayesian model averaging to address the uncertainty of dose-response relationships and enhance the robustness of the design. Additionally, we extend the proposed design to handle delayed toxicity and efficacy outcomes. We conduct extensive simulation studies to evaluate the operating characteristics of the proposed method under various practical scenarios. The results demonstrate that the proposed designs have desirable operating characteristics. A trial example is presented to demonstrate the practical implementation of the proposed designs.

Oncology Dose Selection in Subsequent Indications: What Can We Learn From FDA-approved Oncology Drugs?

PURPOSE

The modern oncology drug development landscape has shifted away from traditional cytotoxic chemotherapies. Following their initial approvals, many oncology drugs have been approved in subsequent indications either as monotherapy or in combination to benefit a broader patient population. To date, dose selection strategies for subsequent indications have not been systematically reviewed. This review examines how approved dosing regimens were selected in subsequent indications for FDA-approved oncology drugs.

METHODS

The Drugs@FDA database was used to identify FDA-approved new molecular entities (NMEs) between 2010 and 2023. NMEs with more than 1 approved indication were included in the analysis. In total, the dosing regimens for 67 novel oncology drugs that obtained FDA approvals for multiple indications were evaluated.

FINDINGS

Overall, in subsequent indications, 72% of NMEs used the same or clinically equivalent alternative dosing regimens to those approved in the initial indications. Amongst the 28% of NMEs that used different dosing regimens, safety/tolerability was the leading cause of a dosing regimen changes in both monotherapy and combination therapy settings. Other factors leading to changes in dosing regimens include differences in tumor biology, disease burden, pharmacokinetics, and overall benefit-risk profiles obtained from dose-finding studies.

IMPLICATIONS

Our analysis highlighted the importance of selecting a safe, tolerable, and yet efficacious dosing regimen for the initial indication as a suboptimal initially approved regimen could lead to dosing regimen changes in later indications. Preclinical and clinical data could be leveraged to understand the pharmacology, pharmacokinetic, and pharmacodynamic differences between indications and thus support dose selection in subsequent indications.

Dose selection of novel anticancer drugs: exposing the gap between selected and required doses

Historically, dose selection of anticancer drugs has mainly been based on establishing the maximum tolerated dose in phase 1 clinical trials with a traditional 3 plus 3 design. In the era of targeted therapies and immune-modulating agents, this approach does not necessarily lead to selection of the most favourable dose. This strategy can introduce potentially avoidable toxicity or inconvenience for patients. Multiple changes in drug development could lead to more rational dose selection, such as use of better predictive preclinical models, adaptive and randomised trial design, evaluation of multiple dose levels in late-phase development, assessment of target activity and saturation, and early biomarker use for efficacy and safety evaluation. In this Review, we evaluate the rationale and validation of dose selection in each phase of drug development for anticancer drugs approved by the European Medicines Agency and US Food and Drug Administration from Jan 1, 2020, to June 30, 2023, and give recommendations for dose optimisation to improve safety and patient convenience. In our evaluation, we classified 20 (65%) of the 31 recently registered anticancer agents as potential candidates for dose optimisation, which could be achieved either by reducing the dose (n=10 [32%]) or adjusting the dosage regimen (n=10 [32%]). Dose selection seemed to be adequately justified for nine (29%) of the drugs, whereas the reviewed data were inconclusive for formulating a recommendation on dose optimisation for two (6%) of the drugs.

Reporting on patient's body mass index (BMI) in recent clinical trials for patients with breast cancer: a systematic review

BACKGROUND

The proportion of patients with breast cancer and obesity is increasing. While the therapeutic landscape of breast cancer has been expanding, we lack knowledge about the potential differential efficacy of most drugs according to the body mass index (BMI). Here, we conducted a systematic review on recent clinical drug trials to document the dosing regimen of recent drugs, the reporting of BMI and the possible exclusion of patients according to BMI, other adiposity measurements and/or diabetes (leading comorbidity of obesity). We further explored whether treatment efficacy was evaluated according to BMI.

METHODS

A search of Pubmed and ClinicalTrials.gov was performed to identify phase I-IV trials investigating novel systemic breast cancer treatments. Dosing regimens and exclusion based on BMI, adiposity measurements or diabetes, documentation of BMI and subgroup analyses according to BMI were assessed.

RESULTS

495 trials evaluating 26 different drugs were included. Most of the drugs (21/26, 81%) were given in a fixed dose independent of patient weight. BMI was an exclusion criterion in 3 out of 495 trials. Patients with diabetes, the leading comorbidity of obesity, were excluded in 67/495 trials (13.5%). Distribution of patients according to BMI was mentioned in 8% of the manuscripts, subgroup analysis was performed in 2 trials. No other measures of adiposity/body composition were mentioned in any of the trials. Retrospective analyses on the impact of BMI were performed in 6 trials.

CONCLUSIONS

Patient adiposity is hardly considered as most novel drug treatments are given in a fixed dose. BMI is generally not reported in recent trials and few secondary analyses are performed. Given the prevalence of patients with obesity and the impact obesity can have on pharmacokinetics and cancer biology, more attention should be given by investigators and study sponsors to reporting patient's BMI and evaluating its impact on treatment efficacy and toxicity.

Deep Learning Insights into the Dynamic Effects of Photodynamic Therapy on Cancer Cells

Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer cells, while logistic growth modelling predicts cellular behavior post-PDT. Rigorous model validation ensures the accuracy of the findings. Cellpose demonstrates significant morphological changes after PDT, affecting cellular proliferation and survival. The reliability of the findings is confirmed by model validation. This deep learning tool enhances our understanding of cancer cell dynamics after PDT. Advanced analytical techniques, such as morphological analysis and growth modeling, provide insights into the effects of PDT on hepatocellular carcinoma (HCC) cells, which could potentially improve cancer treatment efficacy. In summary, the research examines the role of deep learning in optimizing PDT parameters to personalize oncology treatment and improve efficacy.

Utility and impact of quantitative pharmacology on dose selection and clinical development of immuno-oncology therapy

Immuno-oncology (IO) therapies have changed the cancer treatment landscape. Immune checkpoint inhibitors (ICIs) have improved overall survival in 20-40% of patients with malignancies that were previously refractory. Due to the uniqueness in biology, modalities and patient responses, drug development strategies for IO differed from that traditionally used for cytotoxic and target therapies in oncology, and quantitative pharmacology utilizing modeling approach can be applied in all phases of the development process. In this review, we used case studies to showcase how various modeling methodologies were applied from translational science and dose selection through to label change, using examples that included anti-programmed-death-1 (anti-PD-1), anti-programmed-death ligand-1 (anti-PD-L1), anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4), and anti-glucocorticoid-induced tumor necrosis factor receptor-related protein (anti-GITR) antibodies. How these approaches were utilized to support phase I-III dose selection, the design of phase III trials, and regulatory decisions on label change are discussed to illustrate development strategies. Model-based quantitative approaches have positively impacted IO drug development, and a better understanding of the biology and exposure-response relationship may benefit the development and optimization of new IO therapies.

Dose modification dynamics of ponatinib in patients with chronic-phase chronic myeloid leukemia (CP-CML) from the PACE and OPTIC trials

Ponatinib, the only approved all known-BCR::ABL1 inhibitor, is a third-generation tyrosine-kinase inhibitor (TKI) designed to inhibit BCR::ABL1 with or without any single resistance mutation, including T315I, and induced robust and durable responses at 45 mg/day in patients with CP-CML resistant to second-generation TKIs in the PACE trial. However, cardiovascular toxicities, including arterial occlusive events (AOEs), have emerged as treatment-related AEs within this class of TKIs. The OPTIC trial evaluated the efficacy and safety of ponatinib using a novel, response-based, dose-reduction strategy in patients with CP-CML whose disease is resistant to ≥2 TKIs or who harbor T315I. To assess the dose-response relationship and the effect on the safety of ponatinib, we examined the outcomes of patients with CP-CML enrolled in PACE and OPTIC who received 45 mg/day of ponatinib. A propensity score analysis was used to evaluate AOEs across both trials. Survival rates and median time to achieve ≤1% BCR::ABL1IS in OPTIC were similar or better than in PACE. The outcomes of patients with T315I mutations were robust in both trials. Patients in OPTIC had a lower exposure-adjusted incidence of AOEs compared with those in PACE. This analysis demonstrates that response-based dosing for ponatinib improves treatment tolerance and mitigates cardiovascular risk.

Clinical dose rationale of tislelizumab in patients with solid or hematological advanced tumors

Tislelizumab, an anti-programmed cell death protein 1 monoclonal antibody, has demonstrated improved survival benefits over standard of care for multiple cancer indications. We present the clinical rationale and data supporting tislelizumab dose recommendation in patients with advanced tumors. The phase I, first-in-human, dose-finding BGB-A317-001 study (data cutoff [DCO]: August 2017) examined the following tislelizumab dosing regimens: 0.5-10 mg/kg every 2 weeks (q2w), 2-5 mg/kg q2w or q3w, and 200 mg q3w. Similar objective response rates (ORRs) were reported in the 2 and 5 mg/kg q2w or q3w cohorts. Safety outcomes (grade ≥3 adverse events [AEs], AEs leading to dose modification/discontinuation, immune-mediated AEs, and infusion-related reactions) were generally comparable across the dosing range examined. These results, alongside the convenience of a fixed q3w dose, formed the basis of choosing 200 mg q3w as the recommended dosing regimen for further clinical use. Pooled exposure-response (E-R) analyses by logistic regression using data from study BGB-A317-001 (DCO: August 2020) and three additional phase I/II studies (DCOs: 2018-2020) showed no statistically significant correlation between tislelizumab pharmacokinetic exposure and ORR across multiple solid tumor types or classical Hodgkin's lymphoma, nor was exposure associated with any of the safety end points evaluated over the dose range tested. Hence, tislelizumab showed a relatively flat E-R relationship. Overall, the totality of data, including efficacy, safety, and E-R analyses, together with the relative convenience of a fixed q3w dose, provided clinical rationale for the recommended dosing regimen of tislelizumab 200 mg q3w for multiple cancer indications.

Determination and Confirmation of Recommended Ph2 Dose of Amivantamab in Epidermal Growth Factor Receptor Exon 20 Insertion Non-Small Cell Lung Cancer

Amivantamab has demonstrated durable responses with a tolerable safety profile in non-small cell lung cancer with EGFR exon 20 insertions (Ex20ins) who progressed after prior platinum chemotherapy. Data supporting the amivantamab recommended phase II dose (RP2D) in this patient population are presented. Pharmacokinetic (PK) analysis and population PK (PopPK) modeling were conducted using serum concentration data obtained following amivantamab intravenous administration (140-1,750 mg). Pharmacodynamics (PDs) were evaluated using depletion of soluble EGFR and MET. Exposure-response (E-R) analyses were performed using the primary efficacy end point of objective response rate in patients with EGFR Ex20ins. The E-R relationship for safety was explored for adverse events of clinical interest. Amivantamab exhibited linear PKs at 350-1,750 mg dose levels following administration, with no maximum tolerated dose identified. A two-compartment PopPK model with linear clearance adequately described the observed PKs. Body weight was a covariate of clearance and volume of distribution in the central compartment. PopPK modeling showed that a weight-based, 2-tier (< 80 and ≥ 80 kg) dosing strategy reduces PK variability and provides comparable exposure across 2 weight groups, with 87% of patients achieving exposures above the target threshold. The final confirmed RP2D of amivantamab was 1,050 mg for < 80 kg (1,400 mg for ≥ 80 kg) weekly in cycle 1 (28 days) and every 2 weeks thereafter. No significant exposure-efficacy or safety correlation was observed. In conclusion, the amivantamab RP2D is supported by PK, PD, safety, and efficacy analyses. E-R analyses confirmed that the current regimen provides durable efficacy with tolerable safety.

Quantitative Assessment of Ribociclib Exposure-Response Relationship to Justify Dose Regimen in Patients with Advanced Breast Cancer

Ribociclib in combination with endocrine therapy (ET) is a globally approved treatment option for patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) and has demonstrated significantly improved overall survival (OS) in 3 phase 3 clinical trials. To justify the dose regimen and dose modification scheme for patients with ABC, the pharmacokinetic (PK), safety, and efficacy data of ribociclib were analyzed. The data of several phase 1-3 clinical studies were pooled and analyzed to characterize the relationship between exposure (dose or PK) and efficacy (progression-free survival (PFS), time to response, and OS) or safety (neutropenia and QT interval prolongation). The exposure-efficacy analysis showed no apparent relationship between ribociclib exposure and efficacy (PFS and OS), and efficacy analysis by dose reduction showed that patients with ABC continued to benefit from the treatment following dose reduction, supporting the starting dose of 600 mg as well as dose reductions to 400 and 200 mg. The exposure-safety analysis showed that neutropenia and QT prolongation are related to ribociclib exposure that can be effectively managed by individualized dose modification (dose reduction/interruption). Collective evidence from the exposure-response analyses for efficacy and safety support the use of ribociclib in combination with ET partners at the starting dose of 600 mg, and also the effectiveness of individualized dose reductions in managing safety, while maintaining efficacy, in patients with HR+/HER2- ABC. This analysis illustrates the utility of quantitative assessment in justifying dose selection and dose modification for oncology medicines.

Use of patient-reported outcomes (PRO) data to complement exposure-response analysis in early clinical cancer drug development

BACKGROUND

This proof-of-concept retrospective case study investigated whether patient-reported outcomes (PRO) instruments, designed to capture symptomatic adverse event data, could identity a known exposure-response (ER) relationship for safety characterized in an original FDA analysis of an approved anti-cancer agent. PRO instruments have been designed to uniquely quantify the tolerability aspects of exposure-associated symptomatic adverse events. We explored whether standard ER analyses of clinician-reported safety data for symptomatic adverse events could be complemented by ER analysis using PRO data that capture and quantify the tolerability aspects of these same symptomatic adverse events.

METHODS

Exposure-associated adverse event data for diarrhea were analyzed in parallel in 120 patients enrolled in a clinical trial using physician reported Common Terminology Criteria for Adverse Events (CTCAE) and patient-reported symptomatic adverse event data captured by the National Cancer Institute's (NCI) PRO Common Terminology Criteria for Adverse Events (PRO-CTCAE) instrument. Comparative ER analyses of diarrhea were conducted using the same dataset. Results from the CTCAE and PRO-CTCAE ER analyses were assessed for consistency with the ER relationship for diarrhea established in the original NDA using a 750-patient dataset. The analysis was limited to the 120-patient subset with parallel CTCAE and PRO-CTCAE assessments.

RESULTS

Within the same 120-patient dataset, ER analysis using dense, longitudinal PRO-CTCAE-derived data was sensitive to identify the known ER relationship for diarrhea, whereas the standard CTCAE based ER analysis was not.

CONCLUSIONS

ER analysis using PRO assessed symptomatic adverse event data may be a sensitive tool to complement traditional ER analysis. Improved identification of relationships for safety, by including quantification of the tolerability aspect of symptomatic adverse events using PRO instruments, may be useful to improve the sensitivity of exposure response analysis to support early clinical trial dosage optimization strategies, where decision making occurs within limited small patient datasets.

Model-informed dose selection for an investigational human epidermal growth factor receptor 2 antibody-drug conjugate FS-1502 in patients with human epidermal growth factor receptor 2-expressing advanced malignant solid tumours

AIMS

The dose-escalation phase (phase Ia study) of a novel human epidermal growth factor receptor 2 (HER2) antibody-drug conjugate (ADC) FS-1502 included a dose range from 0.1 to 3.5 mg/kg in HER2-expressing advanced malignant solid tumours. However, the defined maximum tolerated dose was not reached. This model-informed approach integrated population pharmacokinetic (PopPK) modelling and exposure-response (E-R) analysis to facilitate dose selection for phase II.

METHODS

The PopPK model was constructed using PK data from 109 Chinese patients who received doses of 0.1-3.5 mg/kg FS-1502 every 3 (Q3W) or 4 weeks during a phase I dose-escalation and dose expansion trial. The structural model consisted of compartment models for FS-1502 and unconjugated monomethyl auristatin F. E-R was explored for the percentage change in tumour size, overall response rate and treatment-related adverse events.

RESULTS

A semi-mechanistic 2-analyte PopPK model was developed. The FS-1502 PK data were best described by a 2-compartment PK model with parallel linear and nonlinear Michaelis-Menten eliminations. The PK of unconjugated monomethyl auristatin F was described by a 2-compartment model with first-order elimination. E-R analysis supported the clinically meaningful efficacy of FS-1502 at 2.3 mg/kg and above. However, 2.3 mg/kg Q3W was considered to have a better benefit-risk balance due to a lower incidence of safety events without a significant reduction in efficacy compared to 3.0 mg/kg Q3W.

CONCLUSION

This PopPK and E-R analysis guided the recommended phase II dose selection of 2.3 mg/kg Q3W and supported body weight-based dosing for an investigational HER2 ADC FS-1502.

PK/PD model-informed dose selection for oncology phase I expansion: Case study based on PF-06939999, a PRMT5 inhibitor

The optimal dose for targeted oncology therapeutics is often not the maximum tolerated dose. Pharmacokinetic/pharmacodynamic (PK/PD) modeling can be an effective tool to integrate clinical data to help identify the optimal dose. This case study shows the utility of population PK/PD modeling in selecting the recommended dose for expansion (RDE) for the first-in-patient (FIP) study of PF-06939999, a small-molecule inhibitor of protein arginine methyltransferase 5. In the dose escalation part of the FIP trial (NCT03854227), 28 patients with solid tumors were administered PF-06939999 at 0.5 mg, 4 mg, 6 mg, or 8 mg once daily (q.d.) or 0.5 mg, 1 mg, 2 mg, 4 mg, or 6 mg twice daily (b.i.d.). Tolerability, safety, PK, PD biomarkers (plasma symmetrical dimethyl-arginine [SDMA]), and antitumor response were assessed. Semimechanistic population PK/PD modeling analyses were performed to characterize the time-courses of plasma PF-06939999 concentrations, plasma SDMA, and platelet counts collected from 28 patients. Platelet counts were evaluated because thrombocytopenia was the treatment-related adverse event with clinical safety concern. The models adequately described the PK, SDMA, and platelet count profiles both at individual and population levels. Simulations suggested that among a range of dose levels, 6 mg q.d. would yield the optimal balance between achieving the PD target (i.e., 78% reduction in plasma SDMA) and staying below an acceptable probability of developing grade ≥3 thrombocytopenia. As a result, 6 mg q.d. was selected as the RDE. The model-informed drug development approach informed the rational dose selection for the early clinical development of PF-06939999.

Assessment of Patient-Reported Outcomes in Industry-Sponsored Phase I Oncology Studies: Considerations for Translating Theory Into Practice

An increasing interest in the identification of optimal dosage for oncology therapies has prompted key opinion leaders and regulators to encourage the integration of patient-reported outcome (PRO) assessments in phase I oncology clinical trials. Although the potential benefits of assessing PROs in early-phase studies have been acknowledged, the difficulties that arise from such a radical shift have been largely overlooked in the public discussion. In this commentary, the authors provide insight into the challenges that industry sponsors face in integrating PRO assessments into phase I oncology trials, with the ultimate goal of facilitating conversations that may help to resolve some of these issues.

Interleukin-10 in cancer immunotherapy: from bench to bedside

Interleukin (IL)-10 was one of the first cytokines to be recognized. However, its functionality in promoting antitumor immunity was described more recently. Context- and concentration-dependent biological effects are the hallmarks of the pleiotropic role of IL-10. Despite reducing tumor-promoting inflammation, IL-10 may have a role in rejuvenating exhausted tumor-resident T cells. Contrary to the assumption that IL-10 produces an immunosuppressive tumor microenvironment (TME), it promotes activation of tumor-resident CD8+ T cells, which aids tumor rejection. Emerging data from published early-Phase trials have shown mixed results in different tumor types. In this review, we summarize the biological effects of IL-10 and highlight the clinical experience using pegilodecakin.

Clinical outcome assessment trends in clinical trials-Contrasting oncology and non-oncology trials

BACKGROUND

Clinical outcome assessments (COAs) are key to patient-centered evaluation of novel interventions and supportive care. COAs are particularly informative in oncology where a focus on how patients feel and function is paramount, but their incorporation in trial outcomes have lagged that of traditional survival and tumor responses. To understand the trends of COA use in oncology and the impact of landmark efforts to promote COA use, we computationally surveyed oncology clinical trials in ClinicalTrials.gov comparing them to the rest of the clinical research landscape.

METHODS

Oncology trials were identified using medical subject heading neoplasm terms. Trials were searched for COA instrument names obtained from PROQOLID. Regression analyses assessed chronological and design-related trends.

RESULTS

Eighteen percent of oncology interventional trials initiated 1985-2020 (N = 35,415) reported using one or more of 655 COA instruments. Eighty-four percent of the COA-using trials utilized patient-reported outcomes, with other COA categories used in 4-27% of these trials. Likelihood of COA use increased with progressing trial phase (OR = 1.30, p < 0.001), randomization (OR = 2.32, p < 0.001), use of data monitoring committees (OR = 1.26, p < 0.001), study of non-FDA-regulated interventions (OR = 1.23, p = 0.001), and in supportive care versus treatment-focused trials (OR = 2.94, p < 0.001). Twenty-six percent of non-oncology trials initiated 1985-2020 (N = 244,440) reported COA use; they had similar COA-use predictive factors as oncology trials. COA use increased linearly over time (R = 0.98, p < 0.001), with significant increases following several individual regulatory events.

CONCLUSION

While COA use across clinical research has increased over time, there remains a need to further promote COA use particularly in early phase and treatment-focused oncology trials.

Considerations for designing trials targeting muscle dysfunction in exercise oncology

Individuals diagnosed with cancer commonly experience a significant decline in muscle mass and physical function collectively referred to as cancer related muscle dysfunction. This is concerning because impairments in functional capacity are associated with an increased risk for the development of disability and subsequent mortality. Notably, exercise offers a potential intervention to combat cancer related muscle dysfunction. Despite this, research is limited on the efficacy of exercise when implemented in such a population. Thus, the purpose of this mini review is to offer critical considerations for researchers seeking to design studies pertaining to cancer related muscle dysfunction. Namely, 1) defining the condition of interest, 2) determining the most appropriate outcome and methods of assessment, 3) establishing the best timepoint (along the cancer continuum) to intervene, and 4) understanding how exercise prescription can be configured to optimize outcomes.

Integration of Pharmacokinetics, Pharmacodynamics, Safety, and Efficacy into Model-Informed Dose Selection in Oncology First-in-Human Study: A Case of Roblitinib (FGF401)

Model-informed dose selection has been drawing increasing interest in oncology early clinical development. The current paper describes the example of FGF401, a selective fibroblast growth factor receptor 4 (FGFR4) inhibitor, in which a comprehensive modeling and simulation (M&S) framework, using both pharmacometrics and statistical methods, was established during its first-in-human clinical development using the totality of pharmacokinetics (PK), pharmacodynamic (PD) biomarkers, and safety and efficacy data in patients with cancer. These M&S results were used to inform FGF401 dose selection for future development. A two-compartment population PK (PopPK) model with a delayed 0-order absorption and linear elimination adequately described FGF401 PK. Indirect PopPK/PD models including a precursor compartment were independently established for two biomarkers: circulating FGF19 and 7α-hydroxy-4-cholesten-3-one (C4). Model simulations indicated a close-to-maximal PD effect achieved at the clinical exposure range. Time-to-progression was analyzed by Kaplan-Meier method which favored a trough concentration (C_trough )-driven efficacy requiring C_trough above a threshold close to the drug concentration producing 90% inhibition of phospho-FGFR4. Clinical tumor growth inhibition was described by a PopPK/PD model that reproduced the dose-dependent effect on tumor growth. Exposure-safety analyses on the expected on-target adverse events, including elevation of aspartate aminotransferase and diarrhea, indicated a lack of clinically relevant relationship with FGF401 exposure. Simulations from an indirect PopPK/PD model established for alanine aminotransferase, including a chain of three precursor compartments, further supported that maximal target inhibition was achieved and there was a lack of safety-exposure relationship. This M&S framework supported a dose selection of 120 mg once daily fasted or with a low-fat meal and provides a practical example that might be applied broadly in oncology early clinical development.

Aiding early clinical drug development by elucidation of the relationship between tumor growth inhibition and survival in relapsed/refractory multiple myeloma patients

Early prognosis of clinical efficacy is an urgent need for oncology drug development. Herein, we systemically examined the quantitative approach of tumor growth inhibition (TGI) and survival modeling in the space of relapsed and refractory multiple myeloma (MM), aiming to provide insights into clinical drug development. Longitudinal serum M-protein and progression-free survival (PFS) data from three phase III studies (N = 1367) across six treatment regimens and different patient populations were leveraged. The TGI model successfully described the longitudinal M-protein data in patients with MM. The tumor inhibition and growth parameters were found to vary as per each study, likely due to the patient population and treatment regimen difference. Based on a parametric time-to-event model for PFS, M-protein reduction at week 4 was identified as a significant prognostic factor for PFS across the three studies. Other factors, including Eastern Cooperative Oncology Group performance status, prior anti-myeloma therapeutics, and baseline serum ß2-microglobulin level, were correlated with PFS as well. In conclusion, patient disease characteristics (i.e., baseline tumor burden and treatment lines) were important determinants of tumor inhibition and PFS in MM patients. M-protein change at week 4 was an early prognostic biomarker for PFS.

A review of patient-reported outcome assessments in registration trials of FDA-approved new oncology drugs (2014-2018)

The Food and Drug Administration (FDA) encourages the assessment of patient-reported outcomes (PROs) in oncology clinical trials. A 2015 review showed that approximately 26% of industry-sponsored oncology trials included assessment of PROs. However, the proportion of recent trials that supported new oncology drug approvals and assessed PROs is unknown. This review found that assessment of PROs was included in about 75% of registration trials that supported 55 new FDA drug approvals during 2014-2018. Patient-reported outcome assessment was included more in randomized controlled trials than in open-label trials (88% vs. 69%, respectively) and more in phase 3 than in phase 2 trials (89% vs. 66%, respectively).

Model-based dose selection to inform translational clinical oncology development of WNT974, a first-in-class Porcupine inhibitor

WNT974 is a potent, selective, and orally bioavailable first‐in‐class inhibitor of Porcupine, a membrane‐bound O‐acyltransferase required for Wnt secretion, currently under clinical development in oncology. A phase I clinical trial is being conducted in patients with advanced solid tumors. During the dose‐escalation part, various dosing regimens, including once or twice daily continuous and intermittent dosing at a dose range of 5–45 mg WNT974 were studied, however, the protocol‐defined maximum tolerated dose (MTD) was not established based on dose‐limiting toxicity. To assist in the selection of the recommended dose for expansion (RDE), a model‐based approach was utilized. It integrated population pharmacokinetic (PK) modeling and exposure–response analyses of a target‐inhibition biomarker, skin AXIN2 mRNA expression, and the occurrence of the adverse event, dysgeusia. The target exposure range of WNT974 that would provide a balance between target inhibition and tolerability was estimated based on exposure–response analyses. The dose that was predicted to yield an exposure within the target exposure range was selected as RDE. This model‐based approach integrated PK, biomarker, and safety data to determine the RDE and represented an alternative as opposed to the conventional MTD approach for selecting an optimal biological dose. The strategy can be broadly applied to select doses in early oncology trials and inform translational clinical oncology drug development.

Exposure-Response Analysis to Support Nivolumab Once Every 4 Weeks Dosing in Combination with Cabozantinib in Renal Cell Carcinoma

PURPOSE

A benefit:risk assessment for a less-frequent nivolumab 480 mg Q4W + cabozantinib 40 mg QD dosing regimen was predicted using modeling and simulation of clinical trial data from nivolumab monotherapy studies and from the nivolumab 240 mg Q2W + cabozantinib 40mg QD dosing regimen, which demonstrated clinical benefit versus sunitinib in previously untreated advanced renal cell carcinoma (aRCC) in the phase III CheckMate 9ER trial (NCT03141177).

EXPERIMENTAL DESIGN

Multivariable Cox proportional-hazards analyses were conducted using nivolumab monotherapy data in previously treated aRCC and data from CheckMate 9ER to evaluate progression-free survival (PFS), overall survival (OS), and grade {greater than or equal to}2 immune-mediated adverse events (IMAEs).

RESULTS

Nivolumab 240 mg Q2W + cabozantinib versus nivolumab showed improvement in PFS (HR, 0.38; 95% CI, 0.31-0.47), OS (HR, 0.63 95% CI, 0.46-0.85), and increased risk of grade {greater than or equal to}2 IMAEs (HR, 2.19; 95% CI, 1.79-2.67). Nivolumab exposure was not a predictor of PFS/OS or grade {greater than or equal to}2 IMAEs. Lower nivolumab clearance, male sex, higher baseline bodyweight, and Karnofsky performance (100) were each associated with PFS/OS improvements. Region and IMDC poor score were negative OS predictors. Age, baseline albumin, and programmed death ligand-1 status were not significant PFS/OS predictors. Cabozantinib was a significant grade {greater than or equal to}2 IMAE predictor, driven by diarrhea and hepatic events. Model-predicted PFS/OS and grade {greater than or equal to}2 IMAE rates were similar (<2.5% difference) for nivolumab 240 mg Q2W + cabozantinib and 480 mg Q4W + cabozantinib.

CONCLUSIONS

Comparable benefit:risk was predicted for nivolumab 480 mg Q4W + cabozantinib and nivolumab 240 mg Q2W + cabozantinib.

Personalised, Rational, Efficacy-Driven Cancer Drug Dosing via an Artificial Intelligence SystEm (PRECISE): A Protocol for the PRECISE CURATE.AI Pilot Clinical Trial

Introduction: Oncologists have traditionally administered the maximum tolerated doses of drugs in chemotherapy. However, these toxicity-guided doses may lead to suboptimal efficacy. CURATE.AI is an indication-agnostic, mechanism-independent and efficacy-driven personalised dosing platform that may offer a more optimal solution. While CURATE.AI has already been applied in a variety of clinical settings, there are no prior randomised controlled trials (RCTs) on CURATE.AI-guided chemotherapy dosing for solid tumours. Therefore, we aim to assess the technical and logistical feasibility of a future RCT for CURATE.AI-guided solid tumour chemotherapy dosing. We will also collect exploratory data on efficacy and toxicity, which will inform RCT power calculations.

Methods and analysis: This is an open-label, single-arm, two-centre, prospective pilot clinical trial, recruiting adults with metastatic solid tumours and raised baseline tumour marker levels who are planned for palliative-intent, capecitabine-based chemotherapy. As CURATE.AI is a small data platform, it will guide drug dosing for each participant based only on their own tumour marker levels and drug doses as input data. The primary outcome is the proportion of participants in whom CURATE.AI is successfully applied to provide efficacy-driven personalised dosing, as judged based on predefined considerations. Secondary outcomes include the timeliness of dose recommendations, participant and physician adherence to CURATE.AI-recommended doses, and the proportion of clinically significant dose changes. We aim to initially enrol 10 participants from two hospitals in Singapore, perform an interim analysis, and consider either cohort expansion or an RCT. Recruitment began in August 2020. This pilot clinical trial will provide key data for a future RCT of CURATE.AI-guided personalised dosing for precision oncology.

Ethics and dissemination: The National Healthcare Group (NHG) Domain Specific Review Board has granted ethical approval for this study (DSRB 2020/00334). We will distribute our findings at scientific conferences and publish them in peer-reviewed journals.

Trial registration number: NCT04522284

Contemporary dose-escalation methods for early phase studies in the immunotherapeutics era

Phase 1 dose-escalation trials are crucial to drug development by providing a framework to assess the toxicity of novel agents in a stepwise and monitored fashion. Despite widely adopted, rule-based dose-escalation methods (such as 3 + 3) are limited in finding the maximum tolerated dose (MTD) and tend to treat a significant number of patients at subtherapeutic doses. Newer methods of dose escalation, such as model-based and model-assisted designs, have emerged and are more accurate in finding MTD. However, these designs have not yet been broadly embraced by investigators. In this review, we summarise the advantages and disadvantages of contemporary dose-escalation methods, with emphasis on model-assisted designs, including time-to-event designs and hybrid methods involving optimal biological dose (OBD). The methods reviewed include mTPI, keyboard, BOIN, and their variations. In addition, the challenges of drug development (and dose-escalation) in the era of immunotherapeutics are discussed, where many of these agents typically have a wide therapeutic window. Fictional examples of how the dose-escalation method chosen can alter the outcomes of a phase 1 study are described, including the number of patients enrolled, the trial's timeframe, and the dose level chosen as MTD. Finally, the recent trends in dose-escalation methods applied in phase 1 trials in the immunotherapeutics era are reviewed. Among 856 phase I trials from 2014 to 2019, a trend towards the increased use of model-based and model-assisted designs over time (OR = 1.24) was detected. However, only 8% of the studies used non-rule-based dose-escalation methods. Increasing familiarity with such dose-escalation methods will likely facilitate their uptake in clinical trials.

Seamless phase I/II design for novel anticancer agents with competing disease progression

Molecularly targeted agents and immunotherapies have prolonged administration and complicated toxicity and efficacy profiles requiring longer toxicity observation windows and the inclusion of efficacy information to identify the optimal dose. Methods have been proposed to either jointly model toxicity and efficacy, or for prolonged observation windows. However, it is inappropriate to address these issues individually in the setting of dose-finding because longer toxicity windows increase the risk of patients experiencing disease progression and discontinuing the trial, with progression defining a competing event to toxicity, and progression-free survival being a commonly used efficacy endpoint. No method has been proposed to address this issue in a competing risk framework. We propose a seamless phase I/II design, namely the competing risks continual reassessment method (CR-CRM). Given an observation window, the objective is to recommend doses that minimize the progression probability, among a set of tolerable doses in terms of toxicity risk. In toxicity-centered stage of the design, doses are assigned based on toxicity alone, and in optimization stage of the design, doses are assigned integrating both toxicity and progression information. Design operating characteristics were examined in a simulation study compared with benchmark performances, including sensitivity to time-varying hazards and correlated events. The method performs well in selecting doses with acceptable toxicity risk and minimum progression risk across a wide range of scenarios.

Pivotal Dose of Pembrolizumab: A Dose-Finding Strategy for Immuno-Oncology

Despite numerous publications emphasizing the value of dose finding, drug development in oncology is dominated by the mindset that higher dose provides higher efficacy. Examples of dose finding implemented by biopharmaceutical firms can change this mindset. The purpose of this article is to outline a pragmatic dose selection strategy for immuno-oncology (IO) and other targeted monoclonal antibodies (mAbs). The approach was implemented for pembrolizumab. Selecting a recommended phase II dose (RP2D) with a novel mechanism of action is often challenging due to uncertain relationships between pharmacodynamics measurements and clinical end points. Additionally, phase I efficacy and safety data are generally inadequate for RP2D selection for IO mAbs. Here, the RP2D was estimated based on phase I (clinical study KN001 A and A2) pharmacokinetics data as the dose required for target saturation, which represents a surrogate for maximal pharmacological effect for antagonist mAbs. Due to limitations associated with collecting and analyzing tumor biopsies, characterizing intratumoral target engagement (TE) is challenging. To overcome this gap, a physiologically-based pharmacokinetic model was implemented to predict intratumoral TE. As tumors are spatially heterogeneous, TE was predicted in well-vascularized and poorly vascularized tumor regions. Additionally, impact of differences in target expression, for example, due to interindividual variability and cancer type, was simulated. Simulations showed that 200 mg every 3 weeks can achieve ≥ 90% TE in clinically relevant scenarios, resulting in the recommendation of 200 mg every 3 weeks as the RP2D. Randomized dose comparison studies (KN001 B2 and D) showing similar efficacy over a fivefold dose/exposure range confirmed the RP2D as the pivotal dose.

Quantifying the limits of CAR T-cell delivery in mice and men

CAR (Chimeric Antigen Receptor) T cells have demonstrated clinical success for the treatment of multiple lymphomas and leukaemias, but not for various solid tumours, despite promising data from murine models. Lower effective CAR T-cell delivery rates to human solid tumours compared to haematological malignancies in humans and solid tumours in mice might partially explain these divergent outcomes. We used anatomical and physiological data for human and rodent circulatory systems to calculate the typical perfusion of healthy and tumour tissues, and estimated the upper limits of immune cell delivery rates across different organs, tumour types and species. Estimated maximum delivery rates were up to 10 000-fold greater in mice than humans yet reported CAR T-cell doses are typically only 10-100-fold lower in mice, suggesting that the effective delivery rates of CAR T cells into tumours in clinical trials are far lower than in corresponding mouse models. Estimated delivery rates were found to be consistent with published positron emission tomography data. Results suggest that higher effective human doses may be needed to drive efficacy comparable to mouse solid tumour models, and that lower doses should be tested in mice. We posit that quantitation of species and organ-specific delivery and homing of engineered T cells will be key to unlocking their potential for solid tumours.

Optimizing the Therapeutic Window of Targeted Drugs in Oncology: Potency-Guided First-in-Human Studies

Many targeted therapies are administered at or near the maximum tolerated dose (MTD). With the advent of precision medicine, a larger therapeutic window is expected. Therefore, dose optimization will require a new approach to early clinical trial design. We analyzed publicly available data for 21 therapies targeting six kinases, and four poly (ADP‐ribose) polymerase inhibitors, focusing on potency and exposure to gain insight into dose selection. The free average steady‐state concentration (C_ss) at the approved dose was compared to the in vitro cell potency (half‐maximal inhibitory concentration (IC₅₀)). Average steady‐state area under the plasma concentration‐time curve, the fraction unbound drug in plasma, and the cell potency were taken from the US drug labels, US and European regulatory reviews, and peer‐reviewed journal articles. The C_ss was remarkably similar to the IC₅₀. The median C_ss/IC₅₀ value was 1.2, and 76% of the values were within 3‐fold of unity. However, three drugs (encorafenib, erlotinib, and ribociclib) had a C_ss/IC₅₀ value > 25. Seven other therapies targeting the same 3 kinases had much lower C_ss/IC₅₀ values ranging from 0.5 to 4. These data suggest that these kinase inhibitors have a large therapeutic window that is not fully exploited; lower doses may be similarly efficacious with improved tolerability. We propose a revised first‐in‐human trial design in which dose cohort expansion is initiated at doses less than the MTD when there is evidence of clinical activity and C_ss exceeds a potency threshold. This potency‐guided approach is expected to maximize the therapeutic window thereby improving patient outcomes.

DDGP vs. SMILE in Relapsed/Refractory Extranodal Natural Killer/T-cell Lymphoma, Nasal Type: A Retrospective Study of 54 Patients

Extranodal natural killer/T-cell lymphoma, nasal type (ENKL) is a rare peripheral T-cell lymphoma that predominantly occurs in Asian and South American populations. The treatment of ENKL has been a challenge for a long time. This study was conducted to compare the clinical efficacy and safety of cisplatin, dexamethasone, gemcitabine, and pegaspargase (DDGP) and methotrexate, dexamethasone, ifosfamide, L-asparaginase, and etoposide (SMILE) regimens for relapsed/refractory ENKL and explore the prognostic factors. From October 2014 to July 2019, 54 patients with relapsed/refractory ENKL who received DDGP or SMILE chemotherapy were retrospectively assessed in this study. Thirty-one patients received DDGP chemotherapy and 23 patients received SMILE chemotherapy. A higher complete response rate was observed in patients treated with DDGP regimen (61.3% vs. 30.4%, P = 0.025). The DDGP group (95% confidence interval (CI) of 5-year progression-free survival (PFS): 24.6-66.2%; 95% CI of 5-year overall survival (OS): 8.5-91.7%) was also significantly associated with longer 5-year PFS and 5-year OS (P = 0.008 for 5-year PFS, P = 0.023 for 5-year OS). More serious leucopenia (P = 0.021), neutropenia (P = 0.041), and allergy (P = 0.040) were observed in the SMILE group. Post-treatment Epstein-Barr virus (EBV)-DNA status (P = 0.001 for PFS, P = 0.018 for OS) was identified as a significant prognostic factor for PFS and OS in multivariate analysis. The present research suggested that compared with SMILE chemotherapy, DDGP chemotherapy can significantly improve the response and survival of relapsed/refractory ENKL with better tolerance. Post-treatment EBV-DNA status was identified as a significant prognostic factor for PFS and OS in relapsed/refractory ENKL.

Population pharmacokinetic analysis of phase 1 bemarituzumab data to support phase 2 gastroesophageal adenocarcinoma FIGHT trial

Purpose

To report population pharmacokinetic (PK) analysis of the phase 1 study (FPA144-001, NCT02318329) and to select a clinical dose and schedule that will achieve an empirical target trough concentration (C_trough) for an anti-fibroblast growth factor receptor 2b antibody, bemarituzumab.

Methods

Nonlinear mixed-effect modeling was used to analyse PK data. In vitro binding affinity and receptor occupancy of bemarituzumab were determined. Simulation was conducted to estimate dose and schedule to achieve an empirical target C_trough in a phase 2 trial (FIGHT, NCT03694522) for patients receiving first-line treatment combined with modified 5-fluourouracil, oxaliplatin and leucovorin (mFOLFOX6) for gastric and gastroesophageal junction adenocarcinoma.

Results

Bemarituzumab PK is best described by a two-compartment model with parallel linear and nonlinear (Michaelis–Menten) elimination from the central compartment. Albumin, gender, and body weight were identified as the covariates on the linear clearance and/or volume of distribution in the central compartment, and no dose adjustment was warranted. An empirical target of bemarituzumab C_trough of ≥ 60 µg/mL was projected to achieve > 95% receptor occupancy based on in vitro data. Fifteen mg/kg every 2 weeks, with a single dose of 7.5 mg/kg on Cycle 1 Day 8, was projected to achieve the target C_trough on Day 15 in 98% of patients with 96% maintaining the target at steady state, which was confirmed in the FIGHT trial.

Conclusion

A projected dose and schedule to achieve the target C_trough was validated in phase 1 of the FIGHT trial which supported selection of the phase 2 dose and schedule for bemarituzumab.

Electronic supplementary material

The online version of this article (10.1007/s00280-020-04139-4) contains supplementary material, which is available to authorized users.

Controlled pharmacokinetic anti-cancer drug concentration profiles lead to growth inhibition of colorectal cancer cells in a microfluidic device

We present a microfluidic device to expose cancer cells to a dynamic, in vivo-like concentration profile of a drug, and quantify efficacy on-chip. About 30% of cancer patients receive drug therapy. In conventional cell culture experiments drug efficacy is tested under static concentrations, e.g. 1 μM for 48 hours, whereas in vivo, drug concentration follows a pharmacokinetic profile with an initial peak and a decline over time. With the rise of microfluidic cell culture models, including organs-on-chips, there are opportunities to more realistically mimic in vivo-like concentrations. Our microfluidic device contains a cell culture chamber and a drug-dosing channel separated by a transparent membrane, to allow for shear stress-free drug exposure and label-free growth quantification. Dynamic drug concentration profiles in the cell culture chamber were controlled by continuously flowing controlled concentrations of drug in the dosing channel. The control over drug concentrations in the cell culture chambers was validated with fluorescence experiments and numerical simulations. Exposure of HCT116 colorectal cancer cells to static concentrations of the clinically used drug oxaliplatin resulted in a sensible dose-effect curve. Dynamic, in vivo-like drug exposure also led to statistically significant lower growth compared to untreated control. Continuous exposure to the average concentration of the in vivo-like exposure seems more effective than exposure to the peak concentration (Cmax) only. We expect that our microfluidic system will improve efficacy prediction of in vitro models, including organs-on-chips, and may lead to future clinical optimization of drug administration schedules.

Characterizing Exposure-Response Relationship for Therapeutic Monoclonal Antibodies in Immuno-Oncology and Beyond: Challenges, Perspectives, and Prospects

Recent data from immuno-oncology clinical studies have shown the exposure-response (E-R) relationship for therapeutic monoclonal antibodies (mAbs) was often confounded by various factors due to the complex interplay of patient characteristics, disease, drug exposure, clearance, and treatment response and presented challenges in characterization and interpretation of E-R analysis. To tackle the challenges, exposure relationships for therapeutic mAbs in immuno-oncology and oncology are reviewed, and a general framework for an integrative understanding of E-R relationship is proposed. In this framework, baseline factors, drug exposure, and treatment response are envisioned to form an interconnected triangle, driving the E-R relationship and underlying three components that compose the apparent relationship: exposure-driven E-R, baseline-driven E-R, and response-driven E-R. Various strategies in data analysis and study design to decouple those components and mitigate the confounding effect are reviewed for their merits and limitations, and a potential roadmap for selection of these strategies is proposed. Specifically, exposure metrics based on a single-dose pharmacokinetic model can be used to mitigate response-driven E-R, while multivariable analysis and/or case control analysis of data obtained from multiple dose levels in a randomized study may be used to account for the baseline-driven E-R. In this context, the importance of collecting data from multiple dose levels, the role of prognostic factors and predictive factors, the potential utility of clearance at baseline and its change over time, and future directions are discussed.

Population Pharmacokinetics of Brentuximab Vedotin in Adult and Pediatric Patients With Relapsed/Refractory Hematologic Malignancies: Model-Informed Hypothesis Generation for Pediatric Dosing Regimens

Prior pharmacokinetic (PK) analyses of the antibody‐drug conjugate (ADC) brentuximab vedotin (1.8 mg/kg every 3 weeks) in pediatric patients with relapsed/refractory hematologic malignancies found that patients aged <12 years exhibited decreased ADC area under the curve (AUC) compared with those aged ≥12 years. This population PK (POPPK) analysis used data from pediatric (NCT01492088) and adult (NCT00430846) studies of brentuximab vedotin to quantify body size effects on ADC exposure. Data were collected from 84 patients with a median age of 25.7 years (range, 7.7‐87.3 years), 34 of whom (40.5%) were aged <18 years; median patient weight was 67 kg (range, 21‐154 kg), and median body surface area was 1.8 m² (range, 0.87‐2.81 m²). ADC PK was described by a linear 3‐compartment model with zero‐order input and first‐order elimination. POPPK modeling indicated that dosing brentuximab vedotin at 1.8 mg/kg every 3 weeks or 1.2 mg/kg every 2 weeks resulted in lower ADC AUC values in small/moderate‐sized pediatric patients (<28 kg and 28‐49 kg, respectively) compared with large pediatric/adult patients (50‐100 kg). Dosing at 71.5 mg/m² every 3 weeks and 47.7 mg/m² every 2 weeks was predicted to achieve comparable AUC values across all body weight ranges and a similar AUC to that in the 50‐ to 100‐kg group at the standard doses of 1.8 mg/kg every 3 weeks and 1.2 mg/kg every 2 weeks, respectively. These results have generated a hypothesis to support evaluation of brentuximab vedotin at 48 mg/m² every 2 weeks in combination with adriamycin, vinblastine, and dacarbazine chemotherapy in an ongoing pediatric trial in frontline Hodgkin lymphoma (NCT02979522).

Slow-, Tight-Binding Inhibition of CYP17A1 by Abiraterone Redefines Its Kinetic Selectivity and Dosing Regimen

Substantial evidence underscores the clinical efficacy of inhibiting CYP17A1-mediated androgen biosynthesis by abiraterone for treatment of prostate oncology. Previous structural analysis and in vitro assays revealed inconsistencies surrounding the nature and potency of CYP17A1 inhibition by abiraterone. Here, we establish that abiraterone is a slow-, tight-binding inhibitor of CYP17A1, with initial weak binding preceding the subsequent slow isomerization to a high-affinity CYP17A1-abiraterone complex. The in vitro inhibition constant of the final high-affinity CYP17A1-abiraterone complex ( ( K _i * = 0.39 nM )yielded a binding free energy of -12.8 kcal/mol that was quantitatively consistent with the in silico prediction of -14.5 kcal/mol. Prolonged suppression of dehydroepiandrosterone (DHEA) concentrations observed in VCaP cells after abiraterone washout corroborated its protracted CYP17A1 engagement. Molecular dynamics simulations illuminated potential structural determinants underlying the rapid reversible binding characterizing the two-step induced-fit model. Given the extended residence time (42 hours) of abiraterone within the CYP17A1 active site, in silico simulations demonstrated sustained target engagement even when most abiraterone has been eliminated systemically. Subsequent pharmacokinetic-pharmacodynamic (PK-PD) modeling linking time-dependent CYP17A1 occupancy to in vitro steroidogenic dynamics predicted comparable suppression of downstream DHEA-sulfate at both 1000- and 500-mg doses of abiraterone acetate. This enabled mechanistic rationalization of a clinically reported PK-PD disconnect, in which equipotent reduction of downstream plasma DHEA-sulfate levels was achieved despite a lower systemic exposure of abiraterone. Our novel findings provide the impetus for re-evaluating the current dosing paradigm of abiraterone with the aim of preserving PD efficacy while mitigating its dose-dependent adverse effects and financial burden. SIGNIFICANCE STATEMENT: With the advent of novel molecularly targeted anticancer modalities, it is becoming increasingly evident that optimal dose selection must necessarily be predicated on mechanistic characterization of the relationships between target exposure, drug-target interactions, and pharmacodynamic endpoints. Nevertheless, efficacy has always been perceived as being exclusively synonymous with affinity-based measurements of drug-target binding. This work demonstrates how elucidating the slow-, tight-binding inhibition of CYP17A1 by abiraterone via in vitro and in silico analyses was pivotal in establishing the role of kinetic selectivity in mediating time-dependent CYP17A1 engagement and eventually downstream efficacy outcomes.

Exposure-Safety Analyses of Talazoparib in Patients With Advanced Breast Cancer and Germline BRCA1/2 Mutations in the EMBRACA and ABRAZO Trials

Poly(ADP-ribose) polymerase inhibitors, such as talazoparib, may affect hematopoiesis. This analysis characterized the relationship between talazoparib exposure and the most common grade ≥ 3 hematopoietic adverse events (AEs) leading to dose modification in the phase 2 (ABRAZO) and phase 3 (EMBRACA) trials. The relationship between time-varying average talazoparib concentration (C_avg,t ), along with other baseline variables, and grade ≥ 3 anemia, thrombocytopenia, and neutropenia were evaluated both by graphical examination and using univariate and multivariate Cox proportional hazard models. The results indicated that higher C_avg,t was associated with a higher risk of anemia and thrombocytopenia. A trend toward an association between higher C_avg,t and neutropenia was observed, although not statistically significant. Higher risk of all tested safety end points was associated with lower baseline hemoglobin. Higher risk of neutropenia was associated with lower baseline absolute neutrophil count and lower body weight. These findings support the proposed management of AEs through talazoparib dosing modification.

Assessing the translational value of pre-clinical studies for clinical response rate in oncology: an exploratory investigation of 42 FDA-approved small-molecule targeted anticancer drugs

PURPOSE

To assess the translational value of anticancer preclinical models, we retrospectively investigated the relationships between preclinical data and clinical response rate for 42 small-molecule targeted anticancer drugs approved by the US FDA from 2001 to 2018.

METHODS

For 42 FDA-approved drugs, relevant pre-clinical (IC₅₀, mouse PK/efficacy) and clinical (overall response rates [ORR], PK) data were extracted from the public domain. Relationships were investigated overall and separately by mechanism of action and solid vs liquid tumors. Binomial-normal regression analysis was performed using R.

RESULTS

A significant correlation was found between the ratio of free human average plasma concentration (hC_ave) at the approved clinical dose to biochemical IC₅₀ and ORR for kinase inhibitors with solid tumor indications (KI_ST). We also identified that, for KI_ST, the ratios of (i) total and (ii) free human-to-mouse average plasma concentration at efficacious doses were correlated to ORR ((i) R² = 0.72, n = 10; (ii) R² = 0.78, n = 10)).

CONCLUSION

Relationships were identified for ratios of efficacious clinical exposures to typical preclinical pharmacology data and ORR for KI_ST in this retrospective analysis. Although the obtained datasets are limited, the relationships demonstrate that a systemic exposure relative to established pre-clinical pharmacology experiments for an investigational KI_ST could be used as a reference to assess if desired efficacy could be achieved. This approach may assist selection of the recommended phase 2 dose (RP2D) of an investigational drug.

Population Pharmacokinetic Modeling and Exposure-Response Assessment for the Antibody-Drug Conjugate Brentuximab Vedotin in Hodgkin's Lymphoma in the Phase III ECHELON-1 Study

The efficacy of the CD30‐directed antibody‐drug conjugate (ADC) brentuximab vedotin was established in combination with chemotherapy as frontline treatment for advanced classical Hodgkin's lymphoma in the randomized phase III ECHELON‐1 study. Population pharmacokinetic (PK) and exposure–response models were developed to quantify sources of PK variability and relationships between exposure and safety/efficacy end points in ECHELON‐1. The influence of patient‐specific factors on the PK of the ADC and the microtubule‐disrupting payload monomethyl auristatin E (MMAE) was investigated; none of the significant covariates had a clinically relevant impact. Exposure–response analyses evaluated relationships between time‐averaged area under the curve (AUC; ADC, MMAE) and efficacy end points (ADC) or safety parameters (ADC, MMAE). Exposure–efficacy analyses supported consistent treatment benefit with brentuximab vedotin across observed exposure ranges. Exposure‐safety analyses supported the recommended brentuximab vedotin starting dose (1.2 mg/kg every 2 weeks), and effective management of peripheral neuropathy and neutropenia with dose modification/reduction and febrile neutropenia with granulocyte colony‐stimulating factor primary prophylaxis.

Impact of Tyrosine Kinase Inhibitor Starting Dose on Outcomes in Patients With Non-Small Cell Lung Cancer

BACKGROUND

Epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) can cause intolerable adverse events in patients with non-small cell lung cancer (NSCLC) and may be prescribed at a lower dose.

OBJECTIVE

Our objective was to analyze the starting doses of oral EGFR and ALK TKIs in patients diagnosed with NSCLC at our institution.

METHODS

We conducted a retrospective chart review with patients on EGFR and ALK TKIs for NSCLC. Patients were categorized into 2 groups: patients initiated on Food and Drug Administration (FDA) standard dose (SD) and patients initiated on a reduced dose (RD). Progression-free survival (PFS), overall survival (OS) and other treatment outcomes were compared between both groups.

RESULTS

Ninety patients were included for analysis. The median time-to-progression for the SD group (n = 67) and RD group (n = 23) were 13.4 months (95% confidence interval [CI]:8.9-15.6) and 15.1 months (95%CI: 5.6-21.5), respectively. Median time-to-death was not estimable for OS. The predicted OS probability at approximately 15 months post treatment initiation for the SD group and RD group was 81.8% and 80.5%, respectively.

CONCLUSION

Patients who initiated TKI therapy at a RD did not have different PFS and 15-month survival outcomes than patients who initiated TKI therapy at the FDA SD.