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2. Landscape analysis of adverse events and dose intensity for FDA approved oncology small molecules.

Author

Collins, Keagan P., Yin, Donghua, Pithavala, Yazdi K., and Mittapalli, Rajendar K.

Abstract

As development of new oncology small molecule therapies is focused mainly on molecularly targeted agents, the dose selection paradigm has shifted from the maximum tolerated dose (MTD)-based approach traditionally utilized with cytotoxic drugs towards determining an optimal dose with long-term tolerability while maintaining efficacy. To assess overall tolerability in recently approved oncology small molecules, we surveyed 54 compounds approved by the FDA since March 2017 with respect to dose intensity, dose modifications, and treatment emergent adverse events (TEAEs). Of the 54 new molecular entities surveyed, only 15 were approved at a label dose equal to the MTD (Label Dose = MTD). Compared to compounds where the label dose was less than the MTD, compounds where the Label Dose = MTD reported overall lower dose intensity and higher dose modifications due to adverse events, though treatment discontinuations due to adverse events were similar. A post-marketing requirement (PMR) for dose optimization was issued for 7 compounds in the dataset, of which 3 were at the Label Dose = MTD. None of these 7 compounds reported a positive exposure-response relationship in efficacy and only 4 reported an exposure-response in safety events. Overall, dose intensity was lower, and incidence of dose modifications, discontinuations, and Grade ≥ 3 TEAEs were higher in compounds issued a PMR vs. the latter. This analysis suggests that while recently approved oncology small molecules have a reasonable relative dose intensity (RDI), the higher incidence of Grade ≥ 3 TEAEs and dose modifications where Label Dose = MTD highlight the continuing need for dose optimization while developing oncology therapeutics. [ABSTRACT FROM AUTHOR]

Published
2025
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7. Dose Optimization in Oncology Drug Development: An International Consortium for Innovation and Quality in Pharmaceutical Development White Paper.

Author

Samineni, Divya, Venkatakrishnan, Karthik, Othman, Ahmed A., Pithavala, Yazdi K., Poondru, Srinivasu, Patel, Chirag, Vaddady, Pavan, Ankrom, Wendy, Ramanujan, Saroja, Budha, Nageshwar, Wu, Michael, Haddish‐Berhane, Nahor, Fritsch, Holger, Hussain, Azher, Kanodia, Jitendra, Li, Meng, Li, Mengyao, Melhem, Murad, Parikh, Apurvasena, and Upreti, Vijay V.

Subjects
ANTINEOPLASTIC agents, DRUG development, CONSORTIA, QUALITY of life, CANCER patients
Abstract

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

Published
2024
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13. Evaluation of the Effect of Lorlatinib on CYP2B6, CYP2C9, UGT, and P-Glycoprotein Substrates in Patients with Advanced Non-Small Cell Lung Cancer.

Author

Chen, Joseph, Bearz, Alessandra, Kim, Dong-Wan, Mamdani, Hirva, Bauman, Jessica, Chiari, Rita, Ou, Sai-Hong Ignatius, Solomon, Benjamin J., Soo, Ross A., Felip, Enriqueta, Shaw, Alice T., Thurm, Holger, Clancy, Jill S., Lee, Kimberly, O'Gorman, Melissa, Tanski, Cherie, and Pithavala, Yazdi K.

Subjects
ANAPLASTIC lymphoma kinase, NON-small-cell lung carcinoma, PHARMACOKINETICS, P-glycoprotein, PROTEIN-tyrosine kinase inhibitors, CYTOCHROME P-450
Abstract

Background and Objective: Lorlatinib is a tyrosine kinase inhibitor approved for the treatment of advanced anaplastic lymphoma kinase–positive non-small cell lung cancer. This study assessed the effect of steady-state lorlatinib on the metabolic enzymes cytochrome P450 (CYP) 2B6, CYP2C9, and uridine 5′-diphospho-glucuronosyltransferase (UGT) and the P-glycoprotein (P-gp) transporter. Methods: Thirty-two patients received a single oral dose of a probe drug on Day − 2 to determine the pharmacokinetics of the probe drug alone. Starting on Day 1, patients received 100 mg oral lorlatinib daily. On Day 15, a single oral dose of the probe drug was administered concurrently with lorlatinib. Pharmacokinetic parameters for these probe substrates were assessed. Results: Plasma exposures of all probe substrates were reduced by lorlatinib compared with the probe alone. The greatest reduction in area under the plasma concentration–time curve from time zero to infinity (AUC∞) and maximum (peak) plasma drug concentration (Cmax) (67% and 63% decrease, respectively) was observed with the P-gp probe substrate fexofenadine. Lorlatinib coadministration also decreased the AUC∞ and Cmax of bupropion (CYP2B6 probe substrate) by 25% and 27%, tolbutamide (CYP2C9 probe substrate) by 43% and 15%, and acetaminophen (UGT probe substrate) by 45% and 28%, respectively. Conclusions: Lorlatinib is a net moderate inducer of P-gp and a weak inducer of CYP2B6, CYP2C9, and UGT after steady state is achieved with daily dosing. Medications that are P-gp substrates with a narrow therapeutic window should be avoided in patients taking lorlatinib; no dose modifications are needed with substrates of CYP2B6, CYP2C9, or UGT. ClinicalTrials.gov: NCT01970865. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Phase II, parallel-design study of preoperative combined modality therapy and the matrix metalloprotease (mmp) inhibitor prinomastat in patients with esophageal adenocarcinoma

Author

Heath, Elisabeth I., Burtness, Barbara A., Kleinberg, Lawrence, Salem, Ronald R., Yang, Stephen C., Heitmiller, Richard F., Canto, Marcia I., Knisely, Jonathan P. S., Topazian, Mark, Montgomery, Elizabeth, Tsottles, Nancy, Pithavala, Yazdi, Rohmiller, Bridget, Collier, Mary, and Forastiere, Arlene A.

Published
2006
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38. Liver Toxicity Observed With Lorlatinib When Combined With Strong CYP3A Inducers: Evaluation of Cynomolgus Monkey as a Nonclinical Model for Assessing the Mechanism of Combinational Toxicity

Author

Hu, Wenyue, primary, Lettiere, Daniel, additional, Tse, Susanna, additional, Johnson, Theodore R, additional, Biddle, Kathleen E, additional, Thibault, Stephane, additional, Palazzi, Xavier, additional, Chen, Joseph, additional, Pithavala, Yazdi K, additional, and Finkelstein, Martin, additional

Published
2021
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45. Dynamic Contrast-Enhanced Magnetic Resonance Imaging As a Pharmacodynamic Measure of Response After Acute Dosing of AG-013736, an Oral Angiogenesis Inhibitor, in Patients With Advanced Solid Tumors: Results From a Phase I Study

Author

Liu, Glenn, Rugo, Hope S., Wilding, George, McShane, Teresa M., Evelhoch, Jeffrey L., Ng, Chaan, Jackson, Edward, Kelcz, Frederick, Yeh, Benjamin M., Lee, Fred T., Jr, Charnsangavej, Chusilp, Park, John W., Ashton, Edward A., Steinfeldt, Heidi M., Pithavala, Yazdi K., Reich, Steven D., and Herbst, Roy S.

Published
2005
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50. Model-based prediction of progression-free survival in patients with first-line renal cell carcinoma using week 8 tumor size change from baseline

Author

Laurent Claret, Pithavala Yazdi, Ying Chen, Pascal Chanu, Francois Mercier, Rene Bruno, Peter A. Milligan, Brad Rosbrook, and Jenny Zheng

Subjects
Sorafenib, Oncology, Niacinamide, Cancer Research, medicine.medical_specialty, Indazoles, Indoles, Time Factors, Axitinib, Antineoplastic Agents, urologic and male genital diseases, Toxicology, 030226 pharmacology & pharmacy, Disease-Free Survival, 03 medical and health sciences, 0302 clinical medicine, Clinical Trials, Phase II as Topic, Renal cell carcinoma, Internal medicine, medicine, Sunitinib, Humans, Pharmacology (medical), Pyrroles, Progression-free survival, Neoplasm Metastasis, Carcinoma, Renal Cell, Randomized Controlled Trials as Topic, Pharmacology, Tumor size, business.industry, Phenylurea Compounds, Hazard ratio, Imidazoles, Interferon-alpha, medicine.disease, Kidney Neoplasms, Logistic Models, Quartile, Clinical Trials, Phase III as Topic, 030220 oncology & carcinogenesis, Multivariate Analysis, business, medicine.drug
Abstract

To assess the link between early tumor shrinkage (ETS) and progression-free survival (PFS) based on historical first-line metastatic renal cell carcinoma (mRCC) data. Tumor size data from 921 patients with first-line mRCC who received interferon-alpha, sunitinib, sorafenib or axitinib in two Phase III studies were modeled. The relationship between model-based estimates of ETS at week 8 as well as the baseline prognostic factors and PFS was tested in multivariate log-logistic models. Model performance was evaluated using simulations of PFS distributions and hazard ratio (HR) across treatments for the two studies. In addition, an external validation was conducted using data from an independent Phase II RCC study. The relationship between expected HR of an investigational treatment vs. sunitinib and the differences in ETS was simulated. A model with a nonlinear ETS-PFS link was qualified to predict PFS distribution by ETS quartiles as well as to predict HRs of sunitinib vs. interferon-alpha and axitinib vs. sorafenib. The model also performed well in simulations of an independent study of axitinib (external validation). The simulations suggested that if a new investigational treatment could further reduce the week 8 ETS by 30 % compared with sunitinib, an expected HR [95 % predictive interval] of the new treatment vs. sunitinib would be 0.59 [0.46, 0.79]. A model has been developed that uses early changes in tumor size to predict the HR for PFS differences between treatment arms for first-line mRCC. Such a model may have utility in predicting the outcome of ongoing studies (e.g., as part of interim futility analyses), supporting early decision making and future study design for investigational agents in development for this indication.

Published
2016

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