ZIC SC 006537 (ZIC) | |||
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Title | Using Clinical Pharmacology Principles to Develop New Anticancer Therapies | ||
Institution | NCI, Bethesda, MD | ||
Principal Investigator | Figg, William | NCI Program Director | N/A |
Cancer Activity | N/A | Division | CCR |
Funded Amount | $732,342 | Project Dates | null - null |
Fiscal Year | 2018 | Project Type | Intramural |
Research Topics w/ Percent Relevance | Cancer Types w/ Percent Relevance | ||
Cancer (100.0%) | N/A | ||
Research Type | |||
Systemic Therapies - Discovery and Development Systemic Therapies - Clinical Applications |
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Abstract | |||
Over the years, the CPP has developed analytical methods for a wide range of therapeutics, numerous which have been published, including depsipeptide, TNP-470, phenylacetate, phenylbutyrate, tamoxifen, UCN-01, CAI, thalidomide, COL-3, suramin, melphalan, erlotinib, perifosine, SU5416, 2ME, MS-275, ketoconazole, lenalidomide, romidepsin, AZD2281 and gemicitabine, sorafenib, finasteride, nelfinavir, 17-DMAG, clopidogrel and and its MPB-derivatized active thiol-metabolite (CAMD), Hsp90 inhibitor PF-04928473, irinotecan (its active metabolite SN38, and glucuronidated SN38), Trk kinase inhibitor AZD7451, pomalidomide, olaparib, sorafenib, belinostat, cediranib, abiraterone, cabozantinib, carfilzomib, midazolam, lapatinib, temozolomide, perifosine, and valproic acid. We have developed a sensitive and selective ultra-high performance liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) method for the quantification of temozolomide in nonhuman primate (NHP) plasma, cerebrospinal fluid (CSF), and brain extracellular fluid (ECF) following microdialysis. We have recently developed a UHPLC-MS/MS assay for simultaneous quantitation of cyclophosphamide and the 4-hydroxycyclophosphamide metabolite in human plasma. Over the years, the CPP has provided PK support for various agents in phase I/II trials: suramin, TNP-470, CAI, UCN-01, docetaxel, flavopiridol, thalidomide, lenalidomide, pomalidomide, intraperitoneal cisplatin/carboplatin, paclitaxel, 17-DMAG, imatinib, sorafenib, nelfinavir, bevacizumab, romidepsin, clopidrogrel, bortezomib, TRC-105, vandetanib, olaparib, topotecan, irinotecan, mithramycin, durvalumab, and abiraterone. During the FY2018, the CPP provided PK support for several phase I/II clinical studies, including a phase I trial of belinostat with cisplatin and etoposide in advanced solid tumors, with a focus on neuroendocrine and small cell cancers of the lung; phase I/II trial and pharmacokinetic study of mithramycin in children and adults with refractory Ewing sarcoma and EWS-FLI1 fusion transcript; a phase II food effect study of abiraterone acetate; a study to evaluate the effect of an adenosine A2A agonist on intratumoral concentrations of temozolomide in patients with recurrent glioblastoma. In order to optimize therapy, a full understanding of the pharmacokinetics of any systemic therapy is desired. We routinely model the pharmacokinetic (PK) data of agents being tested for antitumor activity and correlate that with activity and/or toxicity (pharmacodynamics modeling). We utilize compartmental and noncompartmental approaches to define the disposition of agents. Analysis of PK data (using concentration measurements provided by sample analysis using validated assays) allows for assessment of drug disposition, including the absorption, distribution, metabolism and excretion of a drug. Modeling this data, essentially describing these physiological processes as a mathematical equation, allows for optimization of drug administration (including dose and frequency of dosing,) in silico. Over the years, we have conducted population pharmacokinetic modeling of the following compounds: depsipeptide, romidepsin, sorafenib, olaparib, docetaxel in combination with the p-glycoprotein antagonist tariquidar, TRC105, and TRC102. Recent efforts have focused on building a population PK model to understand the disposition kinetics of mithramycin in the body to best optimize dose. We also performed population PK (PPK) modeling and simulation of belinostat, a second-generation histone deacetylase inhibitor (HDI) predominantly metabolized by UGT1A1-mediated glucuronidation. Two common polymorphisms (UGT1A1*28 and UGT1A1*60) were previously associated with impaired drug clearance and thrombocytopenia risk, likely from increased drug exposure. We conducted a PPK model to include a pharmacodynamic (PD) model describing the change in platelet levels in patients with cancer administered belinostat as a 48-h continuous intravenous infusion |