Early targeted drug development: Pilot FDA review of PI3K inhibitor phase I studies using a knowledge management database.

2011 ◽  
Vol 29 (15_suppl) ◽  
pp. 3060-3060
Author(s):  
G. M. Blumenthal ◽  
R. Charlab Orbach ◽  
I. Zineh ◽  
P. Cortazar ◽  
R. L. Justice ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Drug Development ◽  
Phase I ◽  
Pi3k Inhibitor ◽  
Phase I Studies ◽  
Targeted Drug ◽  
Management Database

scholarly journals Research biopsies in the context of early phase oncology studies: clinical and ethical considerations

2013 ◽  
Vol 7 (1) ◽  
pp. 5 ◽  
Author(s):  
Matilde Saggese ◽  
Divyanshu Dua ◽  
Emily Simmons ◽  
Charlotte Lemech ◽  
Hendrik-Tobias Arkenau
Keyword(s):  
Drug Development ◽  
Phase I ◽  
Tumor Biology ◽  
Biological Response ◽  
Resistance Mechanisms ◽  
Dose Finding ◽  
Direct Result ◽  
Phase I Studies ◽  
Increasing Demand ◽  
Tumor Biopsies

The Personalized Medicine approach in oncology is a direct result of an improved understanding of complex tumor biology and advances in diagnostic technologies. In recent years, there has been an increased demand for archival and fresh tumor analysis in early clinical trials to foster proof-of-concept biomarker development, to understand resistance mechanisms, and ultimately to assess biological response. Although phase I studies are aimed at defining drug safety, pharmacokinetics, and to recommend a phase II dose for further testing, there is now increasing evidence of mandatory tumor biopsies even at the earliest dose-finding stages of drug development. The increasing demand for fresh tumor biopsies adds to the complexity of novel phase I studies and results in different challenges, ranging from logistical support to ethical concerns. This paper investigates key issues, including patients’ perceptions of research biopsies, the need for accurate informed consent, and alternative strategies that may guide the drug development process.

scholarly journals Research biopsies in the context of early phase oncology studies: clinical and ethical considerations

2013 ◽  
pp. e5 ◽  
Author(s):  
Matilde Saggese ◽  
Divyanshu Dua ◽  
Emily Simmons ◽  
Charlotte Lemech ◽  
Hendrik-Tobias Arkenau
Keyword(s):  
Drug Development ◽  
Phase I ◽  
Tumor Biology ◽  
Biological Response ◽  
Resistance Mechanisms ◽  
Dose Finding ◽  
Direct Result ◽  
Phase I Studies ◽  
Increasing Demand ◽  
Tumor Biopsies

The Personalized Medicine approach in oncology is a direct result of an improved understanding of complex tumor biology and advances in diagnostic technologies. In recent years, there has been an increased demand for archival and fresh tumor analysis in early clinical trials to foster proof-of-concept biomarker development, to understand resistance mechanisms, and ultimately to assess biological response. Although phase I studies are aimed at defining drug safety, pharmacokinetics, and to recommend a phase II dose for further testing, there is now increasing evidence of mandatory tumor biopsies even at the earliest dose-finding stages of drug development. The increasing demand for fresh tumor biopsies adds to the complexity of novel phase I studies and results in different challenges, ranging from logistical support to ethical concerns. This paper investigates key issues, including patients’ perceptions of research biopsies, the need for accurate informed consent, and alternative strategies that may guide the drug development process.

Clinical outcomes of adolescents and young adults (AYA) with advanced solid tumors participating in phase I trials.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 10536-10536 ◽  
Author(s):  
Raghav Sundar ◽  
Terri Patricia McVeigh ◽  
Ann Petruckevitch ◽  
Nikolaos Diamantis ◽  
Joo Ern Ang ◽  
...  
Keyword(s):  
Drug Development ◽  
Phase I ◽  
Solid Tumors ◽  
Clinical Outcomes ◽  
Published Data ◽  
Hereditary Cancer Syndrome ◽  
Phase I Trials ◽  
Advanced Solid Tumors ◽  
Phase I Studies ◽  
Development Unit

10536 Background: AYA cancer patients are relatively under-represented in clinical trials, with no published data regarding their outcomes in phase I studies. Trials utilizing novel therapeutic agents are often considered in these patients, due to their tendency to have good organ reserve, and ability to tolerate additional lines of therapy. This study describes the experience of AYA patients with advanced solid tumors treated in a specialized drug development unit. Methods: Patient characteristics and clinical outcomes of AYA patients (defined as age 15 to 39 years at time of initial cancer diagnosis) treated at the Drug Development Unit, Royal Marsden Hospital, United Kingdom, between 2002 and 2016, were captured and analyzed from case and trial records. Results: From a database of 2631 patients treated on phase I trials, 219 AYA patients (8%) were identified. Major tumor types included gynaecological cancer (24%), sarcoma (18%), gastrointestinal (16%) and breast cancer (11%). Patients had a median of 3 previous lines of systemic chemotherapy (range 0 – 6), and 19% participated in 2 or more phase I studies. Twenty (9%) had a known hereditary cancer syndrome (most commonly BRCA), 27% had a family history (FH) of cancer, 15% no FH and 49% no FH documented. Molecular characterization of tumors (n = 45) identified mutations most commonly in p53 (33%) , PI3KCA (18%) and KRAS (9%) . Major trial categories included DNA damage repair (16%), PI3K (16%) and anti-angiogenesis (15%) agents. Grade 3/4 toxicities were experienced in 25% of patients (10% hematological). Of the 214 evaluable patients, objective response rate was 12%, with clinical benefit rate at 6 months of 22%. Median progression free survival was 2.3 months (95% CI: 1.9 to 2.8), median OS was 7.6 months (95% CI: 6.3 to 9.5), and 2-year OS was 11%. Of patients with responses, 35% were matched to phase I trials based on germline or somatic genetic aberrations. Conclusions: A sub-group of AYA patients with advanced solid tumors derive considerable benefit from participating in trials involving novel therapeutics. Future research must focus on predictive biomarkers and molecular profiling to identify those that would benefit from novel therapies.

A mismatch between methods and objectives in phase I drug development: Statistical limitations and personalized medicine—A California Cancer Consortium (CCC) study.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 2538-2538
Author(s):  
Paul Henry Frankel ◽  
Stephen Shibata ◽  
Susan G. Groshen ◽  
Jeff Longmate ◽  
Sumanta Kumar Pal ◽  
...  
Keyword(s):  
Drug Development ◽  
Phase I ◽  
Statistical Methods ◽  
Dose Level ◽  
Patient Selection ◽  
Survey Methods ◽  
Small Sample ◽  
Reliable Estimate ◽  
Phase I Studies ◽  
Grade 3

2538 Background: Patient variation in drug response and toxicity impacts all phases of drug development. While detailed sample-size calculations and analysis based on statistical methodology are critical for addressing variation in late stage trials, phase I studies pose unique and largely unsolved challenges related to variability. Changes in patient selection during the study, small sample-sizes and large patient variation in toxicity are exactly the kind of problems that statistical methods cannot address in small, isolated phase I studies, regardless of apparent mathematical rigor. We have documented these problems via a physician survey. Methods: A 10-question anonymous survey was sent to 670 oncologists at National Comprehensive Cancer Network (NCCN) and CCC institutions via an online survey. 19 % (126/670) of the oncologists polled responded. 78/126 (62%) specialized in Medical Oncology. The number of years in practice varied from 2-45 yrs with a median of 17 yrs. Results: a) 66% of all respondents stated that non-DLT toxicities on one dose level would impact their patient selection on the following dose level, conflicting with the assumption of random patient selection implicit in simulations used in evaluating statistical designs. b) Only 13% stated a desire to target a non-heme toxicity as high as 20% grade 3, while 87% desired a 10% or less grade 3 rate; c) More than half the respondents would prefer not to escalate if 3/3 patients experienced grade 2 LFTs; d) 82% of the respondents thought the appropriate target toxicity differed for patients depending on their potential for becoming a surgical candidate, furthering the need for personalized dosing. Conclusions: Statistical methods in phase I trials are unable to address many of the salient features of phase I study conduct and investigator goals. We will present several approaches we have initiated to address these limitations, and present future plans to help produce a more reliable estimate of a recommended dose. Supported in part by NCI grants U01CA062505, N01-CM-62209, and NCCN data collection assistance.

scholarly journals Romidepsin and lenalidomide based regimens have efficacy in relapsed/refractory lymphoma: combined analysis of two phase I studies with expansion cohorts

2021 ◽  
Author(s):  
Neha Mehta‐Shah ◽  
Matthew A. Lunning ◽  
Alison J. Moskowitz ◽  
Adam M. Boruchov ◽  
Jia Ruan ◽  
...  
Keyword(s):  
Phase I ◽  
Two Phase ◽  
Phase I Studies ◽  
Combined Analysis ◽  
Refractory Lymphoma

scholarly journals The Power of Phase I Studies to Detect Clinical Relevant QTc Prolongation: A Resampling Simulation Study

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Georg Ferber ◽  
Ulrike Lorch ◽  
Jörg Täubel
Keyword(s):  
Phase I ◽  
Healthy Subjects ◽  
Sparse Sampling ◽  
Positive Control ◽  
Qtc Prolongation ◽  
False Negatives ◽  
Assay Sensitivity ◽  
Phase I Studies ◽  
Sufficient Power

Concentration-effect (CE) models applied to early clinical QT data from healthy subjects are described in the latest E14 Q&A document as promising analysis to characterise QTc prolongation. The challenges faced if one attempts to replace a TQT study by thorough ECG assessments in Phase I based on CE models are the assurance to obtain sufficient power and the establishment of a substitute for the positive control to show assay sensitivity providing protection against false negatives. To demonstrate that CE models in small studies can reliably predict the absence of an effect on QTc, we investigated the role of some key design features in the power of the analysis. Specifically, the form of the CE model, inclusion of subjects on placebo, and sparse sampling on the performance and power of this analysis were investigated. In this study, the simulations conducted by subsampling subjects from 3 different TQT studies showed that CE model with a treatment effect can be used to exclude small QTc effects. The number of placebo subjects was also shown to increase the power to detect an inactive drug preventing false positives while an effect can be underestimated if time points aroundtmaxare missed.

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