Biopharmaceutics Applications of Physiologically Based Pharmacokinetic Absorption Modeling and Simulation in Regulatory Submissions to the U.S. Food and Drug Administration for New Drugs.

Physiologically based pharmacokinetic (PBPK) absorption modeling and simulation is increasingly used as a tool in drug product development, not only in support of clinical pharmacology applications (e.g., drug-drug interaction, dose selection) but also from quality perspective, enhancing drug product understanding. This report provides a summary of the status and the application of PBPK absorption modeling and simulation in new drug application (NDA) submissions to the U.S. Food and Drug Administration to support drug product quality (e.g., clinically relevant dissolution specifications, active pharmaceutical ingredient (API) particle size distribution specifications). During the 10 years from 2008 to 2018, a total of 24 NDA submissions included the use of PBPK absorption modeling and simulations for biopharmaceutics-related assessment. In these submissions, PBPK absorption modeling and simulation served as an impactful tool in establishing the relationship of critical quality attributes (CQAs) including formulation variables, specifically in vitro dissolution, to the in vivo performance. This article also summarizes common practices in PBPK approaches and proposes future directions for the use of PBPK absorption modeling and simulation in drug product quality assessment.Graphical abstract.

A Biopharmetrics Approach for Drug Product Quality Control with Clinical Relevance.

To exemplify a systematic and quantitative approach (Biopharmetrics approach) for product quality control with clinical relevance, the study utilized multivariate models to connect raw material attributes of a product to its dissolution obtained in a DOE (design of experiment) and further extended the connection to the in vivo exposures (AUC and Cmax) of the product using an available IVIVC (in vitro/in vivo correlation). Thus, a model for the relationship between in vivo exposure and raw material attributes of the product was established. Based on the model, the exposure ratios between future batches (with various raw material attributes) and the pivotal clinical batches (with confirmed clinical efficacy and safety) were predicted resulting in a set of contour lines in a graphical representation. Among these contour lines, the lines for exposure ratios of 0.8 and 1.2 were defined as lower and upper limits. With the failure edges defined, clinically meaningful limits for the raw material quality control were specified. If the raw material attributes in the future production conform to the specifications, the manufacturing would lead to products bioequivalent to the clinical batches. From these exercises, Biopharmetrics, a subdiscipline of biopharmaceutics, was introduced and its definition, scope, and characteristics were discussed.

Dissolution Edge Charts for Immediate Release Products and Their Applications: a Simulation Study to Aid the Setting of Specifications.

One of the most commonly used methods to establish the clinical relevance of dissolution is to align the dissolution specifications with pivotal clinical batches. The objective of the study was to create edge charts for the dissolution of immediate release (IR) drug products to quantitatively establish the bases for setting clinically relevant and discriminating dissolution specifications and to clarify which stage in the US Pharmacopoeia (USP) <711> acceptance tables should be targeted. The simulations of dissolution data were performed on a batch of IR products with 1,000,000 units. The desired acceptance criterion was Q = 80% of the label claim at 30 min. A total of 110 scenarios for IR data were generated, which included various combinations of two determinants: the batch mean and SD (standard deviation). For each scenario, the dissolution data were tested based on USP three-stage procedures to determine the pass/fail at each stage. This process was repeated 10,000 times. The failure rate at each stage for each scenario was calculated as the percentage of failed replicates across 10,000 trials. Contour plots, named edge charts, were created to demonstrate the relationship between the dissolution failure rates and the two determinants (mean and SD). The edge lines represent the failure rates for the given combinations of the mean and SD. The edge charts can provide a quantitative estimate based on the observed dissolution data and provide fundamental support for recommendations on using USP stage 2 as a target for setting the acceptance limit(s).

Application of Physiologically Based Absorption Modeling to Characterize the Pharmacokinetic Profiles of Oral Extended Release Methylphenidate Products in Adults.

A previously presented physiologically-based pharmacokinetic model for immediate release (IR) methylphenidate (MPH) was extended to characterize the pharmacokinetic behaviors of oral extended release (ER) MPH formulations in adults for the first time. Information on the anatomy and physiology of the gastrointestinal (GI) tract, together with the biopharmaceutical properties of MPH, was integrated into the original model, with model parameters representing hepatic metabolism and intestinal non-specific loss recalibrated against in vitro and in vivo kinetic data sets with IR MPH. A Weibull function was implemented to describe the dissolution of different ER formulations. A variety of mathematical functions can be utilized to account for the engineered release/dissolution technologies to achieve better model performance. The physiological absorption model tracked well the plasma concentration profiles in adults receiving a multilayer-release MPH formulation or Metadate CD, while some degree of discrepancy was observed between predicted and observed plasma concentration profiles for Ritalin LA and Medikinet Retard. A local sensitivity analysis demonstrated that model parameters associated with the GI tract significantly influenced model predicted plasma MPH concentrations, albeit to varying degrees, suggesting the importance of better understanding the GI tract physiology, along with the intestinal non-specific loss of MPH. The model provides a quantitative tool to predict the biphasic plasma time course data for ER MPH, helping elucidate factors responsible for the diverse plasma MPH concentration profiles following oral dosing of different ER formulations.

Scientific and Regulatory Considerations in Solid Oral Modified Release Drug Product Development.

This review presents scientific and regulatory considerations for the development of solid oral modified release (MR) drug products. It includes a rationale for patient-focused development based on Quality-by-Design (QbD) principles. Product and process understanding of MR products includes identification and risk-based evaluation of critical material attributes (CMAs), critical process parameters (CPPs), and their impact on critical quality attributes (CQAs) that affect the clinical performance. The use of various biopharmaceutics tools that link the CQAs to a predictable and reproducible clinical performance for patient benefit is emphasized. Product and process understanding lead to a more comprehensive control strategy that can maintain product quality through the shelf life and the lifecycle of the drug product. The overall goal is to develop MR products that consistently meet the clinical objectives while mitigating the risks to patients by reducing the probability and increasing the detectability of CQA failures.

Regulatory Experience with In Vivo In Vitro Correlations (IVIVC) in New Drug Applications.

In the past two decades, in vitro in vivo correlation (IVIVC) has been considered an important tool for supporting biowaivers, setting dissolution acceptance criteria, and more recently in the Quality by Design (QbD) framework promoting the establishment of clinically meaningful drug product specifications using dissolution as the endpoint. Based on our review experience at the FDA, for the purposes of this article, we analyzed the current state of regulatory submissions containing IVIVC approaches and discussed the successes and failures from the perspectives of study design to methodology. In the past decade, the overall acceptance rate of the IVIVC submissions is about 40%. Moreover, the number of IVIVC studies seen in the submissions per year is not increasing. Establishing clinically meaningful drug product specifications through the linkages between the identified critical quality attributes and in vivo performance is key for developing a quality drug product. To achieve this goal, there is an imminent need for addressing the issues behind a low success rate in IVIVC development. The results from the current analysis revealed that special considerations should be taken in areas such as (1) selection of appropriate number/kind of formulations for IVIVC development/validation, (2) construction of exploratory plots to guide model building and selection, (3) investigation of the reasons of inconclusive predictability, (4) improvement on the quality and richness of the data, and (5) avoidance of over parameterization. The development and incorporation of biopredictive dissolution methods and the use of non-conventional approaches, including mechanistic/physiologically based approaches, should be explored to increase the likelihood of IVIVC success.

Regulatory Perspectives on Strength-Dependent Dissolution Profiles and Biowaiver Approaches for Immediate Release (IR) Oral Tablets in New Drug Applications.

Dissolution profile comparisons are used by the pharmaceutical industry to assess the similarity in the dissolution characteristics of two formulations to decide whether the implemented changes, usually minor/moderate in nature, will have an impact on the in vitro/in vivo performance of the drug product. When similarity testing is applied to support the approval of lower strengths of the same formulation, the traditional approach for dissolution profile comparison is not always applicable for drug products exhibiting strength-dependent dissolution and may lead to incorrect conclusions about product performance. The objective of this article is to describe reasonable biopharmaceutic approaches for developing a biowaiver strategy for low solubility, proportionally similar/non-proportionally similar in composition immediate release drug products that exhibit strength-dependent dissolution profiles. The paths highlighted in the article include (1) approaches to address biowaiver requests, such as the use of multi-unit dissolution testing to account for sink condition differences between the higher and lower strengths; (2) the use of a single- vs. strength-dependent dissolution method; and (3) the use of single- vs. strength-dependent dissolution acceptance criteria. These approaches are cost- and time-effective and can avoid unnecessary bioequivalence studies.

Applications of In Vitro-In Vivo Correlations in Generic Drug Development: Case Studies.

In vitro-in vivo correlation (IVIVC) is a predictive mathematical model describing the relationship between an in vitro property and a relevant in vivo response. The main objective of an IVIVC is to serve as a surrogate for human bioequivalence (BE) studies, which may reduce the number of BE studies performed during the initial approval process as well as with certain scale-up and postapproval changes. The US Food and Drug Administration (FDA) published a regulatory guidance related to development, evaluation, and applications of IVIVC for extended-release (ER) oral dosage forms in September 1997. Despite the publication of this guidance, the deficiencies related to IVIVC are still identified by the Division of Bioequivalence in the process of Abbreviated New Drug Application (ANDA) review. Thus, the main objective of this article is to present the most commonly occurring deficiencies associated with IVIVCs via selected case studies from the ANDAs for oral ER drug products only. We searched internal FDA databases from January 1996 to December 2014 to identify the ANDAs for proposed generic oral ER drug products containing IVIVC. Only 14 ANDA submissions had IVIVC data, and most were not acceptable. Only one ANDA submission included adequate information related to IVIVC data enabling the completion of BE review within first review cycle. It is hoped that awareness of the deficiencies presented in our article would help the generic drug applicants to submit complete and appropriate information related to IVIVC data, ultimately, resulting in a more timely approval of ANDAs.

Influence of drug property and product design on in vitro-in vivo correlation of complex modified-release dosage forms.

The present study examines how drug's inherent properties and product design influence the evaluation and applications of in vitro-in vivo correlation (IVIVC) for modified-release (MR) dosage forms consisting of extended-release (ER) and immediate-release (IR) components with bimodal drug release. Three analgesic drugs were used as model compounds, and simulations of in vivo pharmacokinetic profiles were conducted using different release rates of the ER component and various IR percentages. Plasma concentration-time profiles exhibiting a wide range of tmax and maximum observed plasma concentration (Cmax) were obtained from superposition of the simulated IR and ER profiles based on a linear IVIVC. It was found that depending on the drug and dosage form design, direct use of the superposed IR and ER data for IVIVC modeling and prediction may (1) be acceptable within errors, (2) become unreliable and less meaningful because of the confounding effect from the non-negligible IR contribution to Cmax, or (3) be meaningless because of the insensitivity of Cmax to release rate change of the ER component. Therefore, understanding the drug, design and drug release characteristics of the product is essential for assessing the validity, accuracy, and reliability of IVIVC of complex MR products obtained via directly modeling of in vivo data.

Vandetanib for the treatment of symptomatic or progressive medullary thyroid cancer in patients with unresectable locally advanced or metastatic disease: U.S. Food and Drug Administration drug approval summary.

On April 6, 2011, the U.S. Food and Drug Administration approved vandetanib (Caprelsa tablets; AstraZeneca Pharmaceuticals LP) for the treatment of symptomatic or progressive medullary thyroid cancer in patients with unresectable, locally advanced, or metastatic disease. Vandetanib is the first drug approved for this indication, and this article focuses on the basis of approval. Approval was based on the results of a double-blind trial conducted in patients with medullary thyroid carcinoma. Patients were randomized 2:1 to vandetanib, 300 mg/d orally (n = 231), or to placebo (n = 100). The primary objective was demonstration of improvement in progression-free survival (PFS) with vandetanib compared with placebo. Other endpoints included evaluation of overall survival and objective response rate. The PFS analysis showed a marked improvement for patients randomized to vandetanib (hazard ratio = 0.35; 95% confidence interval, 0.24-0.53; P < 0.0001). The objective response rate for the vandetanib arm was 44% compared with 1% for the placebo arm. The most common grade 3 and 4 toxicities (>5%) were diarrhea and/or colitis, hypertension and hypertensive crisis, fatigue, hypocalcemia, rash, and corrected QT interval (QTc) prolongation. This approval was based on a statistically significant and clinically meaningful improvement in PFS. Given the toxicity profile, which includes prolongation of the QT interval and sudden death, only prescribers and pharmacies certified through the vandetanib Risk Evaluation Mitigation Strategy Program are able to prescribe and dispense vandetanib. Treatment-related risks should be taken into account when considering the use of vandetanib in patients with indolent, asymptomatic, or slowly progressing disease.

In vivo bioequivalence and in vitro similarity factor (f2) for dissolution profile comparisons of extended release formulations: how and when do they match?

PURPOSE: To investigate how likely two extended release formulations are to be bioequivalent when they demonstrate f2 similarity. METHOD: Dissolution profiles were simulated using the Weibull model and varying model parameters around those of a reference profile. The f2 values were calculated for the comparisons of each simulation with the reference profile. The in vivo inputs obtained from an in vitro-in vivo correlation model were convolved with a unit impulse response function. The AUC, Cmax, and Tmax from each simulated in vivo concentration profile were compared to the reference profile. The AUCR (AUC ratio) and CmaxR (Cmax ratio) were determined. The consistency between f2 and bioequivalence was investigated. RESULTS: The relationships between AUCR, CmaxR, f2 and the Weibull model parameters demonstrate that the bioequivalence regions enclosed by the contour lines of 80% and 125% of AUCR and CmaxR were generally close to the regions enclosed by the f2 = 50 contour line, but did not exactly match, especially when Dmax and B deviated from the reference values. CONCLUSIONS: When f2 is used for in vitro dissolution profile comparison, the completeness of the dissolution profiles should not differ more than 10%, and the shapes of the dissolution profiles should not be significantly different.

Bioavailability considerations in evaluating drug-drug interactions using the population pharmacokinetic approach.

Applying a comedication (COMD) covariate to apparent clearance (CL(app) = CL/F) is a common practice when using population pharmacokinetics (PopPK) to study metabolism-based drug-drug interactions (DDI). This study evaluates the importance of independently applying COMD to F and CL to account for DDI at the level of first-pass metabolism. A known DDI between single oral doses of the CYP3A substrate midazolam (5 mg) and the inhibitor ketoconazole (400 mg) was simulated using a physiologically based pharmacokinetic simulator SimCyp in virtual subjects. The simulated midazolam data were analyzed by PopPK method under the following scenarios by applying COMD effect to (1) CL(app) only, (2) CL and F, and (3) CL(app) and apparent volume of distribution (V(app) = V/F), assuming V is unchanged. The mean simulated degree of interaction, measured by midazolam AUC ratio with and without ketoconazole (AUCR), was 10.28. Scenario 1 underestimated AUCR. When COMD was independently applied to F and V(app) in scenarios 2 and 3, lower objective function values of the PopPK analysis and more accurate AUCR estimates were achieved. AUCR estimates were also dependent on sampling. The authors conclude that when significant inhibition of the first-pass metabolism of the substrate is anticipated, COMD effects should be applied to both CL and F in PopPK analysis.

Drug-drug interaction pattern recognition.

BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is an important aspect of drug development, especially for safety. When a drug is used concomitantly with other drug(s), one of the major concerns is the change of exposures, including the rate and extent of drug absorption, distribution, metabolism and elimination. To address the concerns, a common practice is to measure and report the differences between the exposure in the presence and in the absence of concomitant medication (COMED). The area under the plasma concentration versus time curve (AUC), maximum plasma concentration (C(max)) and time to reach the C(max) (t(max)) changes are usually measured in DDI studies. A usual observation is the different extents of changes among AUC, C(max) and t(max), which may raise concerns in certain therapeutic areas or some special agents. The objective of this study was to investigate the variation among changes of AUC, C(max) and t(max) in DDI studies, and its pharmacokinetic manifestation. DATA SOURCES: Based on a list of DDI results from the literature, with the assumptions that the primary parameters of a drug of interest were altered during a DDI, two sets of simulated data were generated according to a single oral dose, one-compartment model. The first set including 24 cases with different half-lives and absorption constants (k(a)) considered the exposure changes upon independent variation of bioavailability (F), clearance (CL), volume of distribution (V(d)) and k(a) up to 50-fold increases or decreases. The second set considered the exposure changes with simultaneous variation of F, CL, V(d), and k(a) within 5-fold range (increase or decrease) for a case selected from the first set. STUDY SELECTION, DATA EXTRACTION AND SYNTHESIS: Parameter fold changes (defined in a fashion showing fold increase or fold decreases, including CL fold change, F fold change, V(d) fold change and k(a) fold change) and exposure changes (AUC fold change, C(max) fold change, t(max) fold change and fold change difference [AUC fold change - C(max) fold change]) were used to generate plots demonstrating various relationships between parameter fold changes and exposure changes. Based on the observations that AUC was influenced by CL and F, C(max) was affected by all four parameters, t(max) was mainly determined by CL and k(a), F did little for t(max) and k(a) was unrelated to AUC, a chart was created for DDI pattern recognition. CONCLUSION: An approach, named DDI pattern recognition, is proposed for didactical purposes. It provides a quick initial estimate for interpreting the DDI results based on the exposure changes. This approach entails the following stages: (i) performing a drug interaction study; (ii) calculating the exposure changes in the presence of COMED compared to those in the absence of COMED, and the fold change difference; (iii) selecting the parameter fold changes that may play important roles in a specific DDI, by estimating their possible ranges; and (iv) interpreting the DDI by integrating all the information available, such as the possible mechanism involved. A quicker and better understanding about the processes, which dominate a DDI, has been achieved using this approach by focusing on integration of all information available and mechanistic interpretation.

Two commonly used methods for exposure-adverse events analysis: comparisons and evaluations.

The purpose of this study is to compare and evaluate logistic regression and time-to-event analysis, 2 commonly used methods for exposure-adverse event (AE) analyses. An AE data set selected from clinical trials is analyzed by both methods and the results are compared. The parameter estimates, odds ratios for logistic regression, and hazard ratios for time-to-event analysis for each AE are compared and further analyzed. In a data set involving 822 patients, 25 AEs are analyzed. A linear relationship is demonstrated between the parameter estimates from the 2 methods and between the odds ratios and hazard ratios. The small differences between the 2 analyses are related to the lower rate of the events and the weaker effects of the risk factors. Although the 2 methods can make predications for the risks, the severity, duration, and recurrence are not well defined. AE time profiles showing the onset, duration, and offset of AEs are important for risk assessment and management. Both analyses can provide information about exposure-AE relationship, and the results from the 2 analyses are consistent in most cases. One should not use the logistic model when length of follow-up varies because of biased estimates. The application of the 2 methods should be combined with AE profiling.

Population pharmacokinetics with a very small sample size.

The objective of this study was to evaluate whether pharmacokinetic parameters (clearance and volume of distribution of the central compartment) from a sparse sampling population pharmacokinetic study can be obtained with a very small sample size. For this study, three drugs were selected from the literature. The pharmacokinetics of all three drugs were studied in healthy adult subjects and plasma concentrations versus time data for individual subjects from extensive blood sampling were available. For population PK analysis, only five subjects were chosen and each subject gave either one or two blood samples. The estimated PK parameters from population PK analysis were compared with the PK parameters obtained from extensive sampling. The results of the study indicated that a reasonable estimate of PK parameters can be obtained with two blood samples from each subject with a sample size of five. The population PK study with sparse sampling scheme may be useful for PK studies in neonates and very young children and in subjects with rare diseases where sample size is small.

Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications.

The value of quantitative thinking in drug development and regulatory review is increasingly being appreciated. Modeling and simulation of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression is often referred to as the pharmacometrics analyses. The objective of the current report is to assess the role of pharmacometrics at the US Food and Drug Administration (FDA) in making drug approval and labeling decisions. The New Drug Applications (NDAs) submitted between 2000 and 2004 to the Cardio-renal, Oncology, and Neuropharmacology drug products divisions were surveyed. For those NDA reviews that included a pharmacometrics consultation, the clinical pharmacology scientists ranked the impact on the regulatory decision(s). Of about a total of 244 NDAs, 42 included a pharmacometrics component. Review of NDAs involved independent, quantitative evaluation by FDA pharmacometricians, even when such analysis was not conducted by the sponsor. Pharmacometric analyses were pivotal in regulatory decision making in more than half of the 42 NDAs. Of the 14 reviews that were pivotal to approval related decisions, 5 identified the need for additional trials, whereas 6 reduced the burden of conducting additional trials. Collaboration among the FDA clinical pharmacology, medical, and statistical reviewers and effective communication with the sponsors was critical for the impact to occur. The survey and the case studies emphasize the need for early interaction between the FDA and sponsors to plan the development more efficiently by appreciating the regulatory expectations better.

Approval summary for erlotinib for treatment of patients with locally advanced or metastatic non-small cell lung cancer after failure of at least one prior chemotherapy regimen.

PURPOSE: To describe the Food and Drug Administration (FDA) review and approval of erlotinib (Tarceva, OSI Pharmaceuticals, Melville, NY) for treatment of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) after failure of at least one prior chemotherapy regimen. EXPERIMENTAL DESIGN: The FDA reviewed raw data in electronic format from a randomized controlled clinical trial comparing erlotinib with placebo in patients with locally advanced or metastatic NSCLC after failure of at least one prior chemotherapy regimen. RESULTS: Patients were randomized in a 2:1 ratio (erlotinib, n = 488 and placebo, n = 243). Erlotinib was superior to placebo for survival, progression-free survival, and tumor response rate. Exploratory analyses indicate that epidermal growth factor receptor status may be an important predictor of the erlotinib survival effect. Rash (75% versus 17%) and diarrhea (54% versus 18%) in the erlotnib and placebo group respectively were the most common adverse events. Severe rash occurred in 9% and severe diarrhea in 6% of erlotinib-treated patients and each resulted in study discontinuation in 1% of patients. Dose reductions were required for 10% of patients with rash and 4% of patients with diarrhea. CONCLUSIONS: On November 18, 2004, the FDA granted erlotinib regular approval for treatment of patients with locally advanced or metastatic NSCLC after failure of at least one prior chemotherapy regimen. The applicant has committed to conduct post-marketing clinical trials to assess further the effect of epidermal growth factor receptor expression, measured with immunohistochemical staining, on erlotinib treatment effect.

Approval summary for imatinib mesylate capsules in the treatment of chronic myelogenous leukemia.

PURPOSE: Chronic myelogenous leukemia (CML) results from the breakpoint cluster region-Abl fusion gene product, a tyrosine kinase involved in cell division and apoptosis. Imatinib, an orally administered inhibitor of the breakpoint cluster region-Abl tyrosine kinase, is capable of blocking proliferation and inducing apoptosis in CML cell lines. In this report, we describe the preclinical profile of imatinib and the data submitted in the New Drug Application that led to its marketing approval. EXPERIMENTAL DESIGN: Chemistry manufacturing and controls, animal toxicology, and biopharmaceutical data are described. Results of Phase I and Phase II clinical studies in patients with CML in blast crisis (CML-BC), in accelerated phase (CML-AP), and in chronic phase disease-resistant or intolerant to IFN-alpha (CML-CP) are summarized. The basis for marketing approval and postmarketing commitments by the pharmaceutical company are discussed. RESULTS: Toxicology studies in the rat, dog, and monkey show the hematological, renal, and hepatobiliary toxicity of imatinib. Pharmacokinetic studies in patients with CML demonstrate 98% imatinib bioavailability. The elimination half-lives of the parent drug and the major active metabolite, CGP74588, from plasma are approximately 18 and 40 h, respectively. Approximately 81% of the drug is eliminated in 7 days, 68% in the feces and 13% in the urine. Cytochrome P-450 3A4 is the main enzyme responsible for imatinib metabolism. Phase I and II clinical studies were conducted. The Phase I study, in 83 CML patients, evaluated oral imatinib doses from 25 to 1000 mg/day. Dose-limiting toxicity was not observed. The three Phase II studies, in CML-CP, CML-AP, and CML-BC, enrolled 1027 patients. CML-CP patients received 400 mg/day imatinib, whereas CML-AP and CML-BC patients generally received 600 mg/day imatinib. Primary study endpoints were cytogenetic response rate (CML-CP) and hematological response rate (CML-AP and CML-BC). The cytogenetic response rate for CML-CP patients was 49%. The hematological response rate of CML-AP and CML-BC patients was 63 and 26%, respectively. The most common imatinib adverse events were nausea, vomiting, myalgia, edema, and diarrhea. Elevated liver enzymes and/or bilirubin were reported in 27 patients (2.6%). CONCLUSIONS: On May 10, 2001, imatinib mesylate (Gleevec, formerly known as STI-571 and Glivec), manufactured and distributed by Novartis Pharmaceuticals, East Hanover, NJ, was approved by the United States Food and Drug Administration for the treatment of CML in three clinical settings: CML-BC, CML-AP, and CML-CP. This report summarizes the Food and Drug Administration's review of the New Drug Application.