A biopharmaceutical classification-based Right-First-Time formulation approach to reduce human pharmacokinetic variability and project cycle time from First-In-Human to clinical Proof-Of-Concept.

A Right-First-Time approach is described for developing bona fide formulations for First-In-Human (FIH) to Proof-Of-Concept (POC) studies to meet an overarching goal of reduced project cycle time from IND to NDA (as short as four years). Bona fide formulations are tailor-made according to the drug's biopharmaceutical properties including solubility, permeability and stability. Solubilization techniques are used extensively to reduce oral absorption variability for most compounds. Bona fide formulations contain all necessary functional excipients such as diluent, solubilizer, stabilizer, pH adjuster, disintegrant and lubricant so formulation changes are minimized to avoid significant PK bridging studies. Cycle time of FIH formulation development is aligned with IND-enabling toxicology studies, generally 4-6 months. Resources range from 0.5 full time equivalents (FTE) for a BCS-1 compound to 3 FTE for a BCS-4 compound with high drug delivery hurdles. We have achieved our goal by taking the same formulation from FIH to POC 90% of the time and maintaining the same formulation platform from POC to commercial manufacturing 80% of the time in the past eight years. This strategy enables cycle time reduction from 7 to 4 years for IND to NDA by overlapping clinical study phases and eliminating clinical downtime due to PK bridging studies.

PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach.

The objective of this study is to assess the effectiveness of physiologically based pharmacokinetic (PBPK) models for simulating human plasma concentration-time profiles for the unique drug dataset of blinded data that has been assembled as part of a Pharmaceutical Research and Manufacturers of America initiative. Combinations of absorption, distribution, and clearance models were tested with a PBPK approach that has been developed from published equations. An assessment of the quality of the model predictions was made on the basis of the shape of the plasma time courses and related parameters. Up to 69% of the simulations of plasma time courses made in human demonstrated a medium to high degree of accuracy for intravenous pharmacokinetics, whereas this number decreased to 23% after oral administration based on the selected criteria. The simulations resulted in a general underestimation of drug exposure (Cmax and AUC0- t ). The explanations for this underestimation are diverse. Therefore, in general it may be due to underprediction of absorption parameters and/or overprediction of distribution or oral first-pass. The implications of compound properties are demonstrated. The PBPK approach based on in vitro-input data was as accurate as the approach based on in vivo data. Overall, the scientific benefit of this modeling study was to obtain more extensive characterization of predictions of human PK from PBPK methods.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance.

The objective of this study was to evaluate the performance of various allometric and in vitro-in vivo extrapolation (IVIVE) methodologies with and without plasma protein binding corrections for the prediction of human intravenous (i.v.) clearance (CL). The objective was also to evaluate the IVIVE prediction methods with animal data. Methodologies were selected from the literature. Pharmaceutical Research and Manufacturers of America member companies contributed blinded datasets from preclinical and clinical studies for 108 compounds, among which 19 drugs had i.v. clinical pharmacokinetics data and were used in the analysis. In vivo and in vitro preclinical data were used to predict CL by 29 different methods. For many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. In addition, 66 methods of predicting oral (p.o.) area under the curve (AUCp.o. ) were evaluated for 107 compounds using rational combinations of i.v. CL and bioavailability (F), and direct scaling of observed p.o. CL from preclinical species. Various statistical and outlier techniques were employed to assess the predictability of each method. Across methods, the maximum success rate in predicting human CL for the 19 drugs was 100%, 94%, and 78% of the compounds with predictions falling within 10-fold, threefold, and twofold error, respectively, of the observed CL. In general, in vivo methods performed slightly better than IVIVE methods (at least in terms of measures of correlation and global concordance), with the fu intercept method and two-species-based allometry (rat-dog) being the best performing methods. IVIVE methods using microsomes (incorporating both plasma and microsomal binding) and hepatocytes (not incorporating binding) resulted in 75% and 78%, respectively, of the predictions falling within twofold error. IVIVE methods using other combinations of binding assumptions were much less accurate. The results for prediction of AUCp.o. were consistent with i.v. CL. However, the greatest challenge to successful prediction of human p.o. CL is the estimate of F in human. Overall, the results of this initiative confirmed predictive performance of common methodologies used to predict human CL.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach.

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 1: goals, properties of the PhRMA dataset, and comparison with literature datasets.

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 2: comparative assessment of prediction methods of human volume of distribution.

The objective of this study was to evaluate the performance of various empirical, semimechanistic and mechanistic methodologies with and without protein binding corrections for the prediction of human volume of distribution at steady state (Vss ). PhRMA member companies contributed a set of blinded data from preclinical and clinical studies, and 18 drugs with intravenous clinical pharmacokinetics (PK) data were available for the analysis. In vivo and in vitro preclinical data were used to predict Vss by 24 different methods. Various statistical and outlier techniques were employed to assess the predictability of each method. There was not simply one method that predicts Vss accurately for all compounds. Across methods, the maximum success rate in predicting human Vss was 100%, 94%, and 78% of the compounds with predictions falling within tenfold, threefold, and twofold error, respectively, of the observed Vss . Generally, the methods that made use of in vivo preclinical data were more predictive than those methods that relied solely on in vitro data. However, for many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. It is recommended to initially use the in vitro tissue composition-based equations to predict Vss in preclinical species and humans, putting the assumptions and compound properties into context. As in vivo data become available, these predictions should be reassessed and rationalized to indicate the level of confidence (uncertainty) in the human Vss prediction. The top three methods that perform strongly at integrating in vivo data in this way were the Øie-Tozer, the rat -dog-human proportionality equation, and the lumped-PBPK approach. Overall, the scientific benefit of this study was to obtain greater characterization of predictions of human Vss from several methods available in the literature.

Performance qualification of a new hypromellose capsule: Part II. Disintegration and dissolution comparison between two types of hypromellose capsules.

This Part II paper describes the disintegration and dissolution aspects of the qualification of a new hypromellose capsule (HPMC Shell 2). This new capsule does not contain any gelling agent, and is manufactured by a thermal gelation process. Rupture time of the carrageenan-containing capsule (HPMC Shell 1) and HPMC Shell 2, as measured by an improved real-time detection method, showed only slight differences that did not manifest in vivo. The absence of a gelling agent appeared to give HPMC Shell 2 advantages in dissolution in acidic media and in buffers containing potassium ions. Slow drug release of HPMC Shell 1 in 0.1M HCl was attributed to the interaction of carrageenan with drug compounds; whereas the presence of potassium ions, a gelling promoter for carrageenan, caused delay in capsule opening and larger capsule-to-capsule variation. Disintegration and dissolution performances of both hypromellose capsules are comparable in other dissolution media tested. Based on the superior dissolution performances and quality attributes in terms of physical, mechanical and processability that were detailed in Paper I, the new hypromellose capsule was satisfactorily qualified and has since been used in nearly 20 investigational new drug (IND) compounds.

Asymmetry effect of particle size distribution on content uniformity and over-potency risk in low-dose solid drugs.

Most active pharmaceutical ingredients (API) exhibit particle size distributions with some degrees of asymmetry deviating from log-normality. A new log-skew-normal (L-S-N) distribution model is proposed for a systematic comparison of the asymmetry effect on content uniformity. The new model originated from the S-N model used by Azzalini gives a close approximation to real API particle size distribution. Monte-Carlo method was employed to simulate the dosage potency distribution. A high risk of over potency is uncovered when either the dose is low or API particle size distribution is positively skewed. This is due to the formation of pseudo heavy tail in potency distribution that decays slower than exponentially. Nomographs of API particle size versus dosage strength were constructed with a range of geometric standard deviations and asymmetry parameters with and without particle size cut-off (sieving) for a combined 99% pass rate against USP <905> Uniformity of Dosage Units. It was found that for a given specification of volume median and 90% diameters (d(50) and d(90)), the dosage strength must increase by 10 times if the API asymmetry parameter changes from 1 (log-normal) to 1.1.

Solid dispersion of acetaminophen and poly(ethylene oxide) prepared by hot-melt mixing.

In this study, a model drug, acetaminophen (APAP), was melt mixed with poly(ethylene oxide) (PEO) using a Brabender mixer. APAP was found to recrystallize upon cooling to room temperature for all the drug loadings investigated. Higher drug loading leads to faster recrystallization rate. However, the morphology of the recrystallized drug crystals is identical in samples with different drug loadings and does not change with the storage time. To adjust the drug's dissolution rate, nanoclay Cloisite 15A and 30B were added into the binary mixture. The presence of either of the nanoclay dramatically accelerates the drug's recrystallization rate and slows down the drug's releasing rate. The drop of the releasing rate is mainly due to the decrease of wettability, as supported by the contact angle data. Data analysis of the dissolution results suggests that the addition of nanoclays changes the drug's release mechanism from erosion dominant to diffusion dominant. This study suggests that nanoclays may be utilized to tailor the drug's releasing rate and to improve the dosage form's stability by dramatically shortening the lengthy recrystallization process.

Indole cytosolic phospholipase A2 alpha inhibitors: discovery and in vitro and in vivo characterization of 4-{3-[5-chloro-2-(2-{[(3,4-dichlorobenzyl)sulfonyl]amino}ethyl)-1-(diphenylmethyl)-1H-indol-3-yl]propyl}benzoic acid, efipladib.

The optimization of a class of indole cPLA 2 alpha inhibitors is described herein. The importance of the substituent at C3 and the substitution pattern of the phenylmethane sulfonamide region are highlighted. Optimization of these regions led to the discovery of 111 (efipladib) and 121 (WAY-196025), which are shown to be potent, selective inhibitors of cPLA 2 alpha in a variety of isolated enzyme assays, cell based assays, and rat and human whole blood assays. The binding of these compounds has been further examined using isothermal titration calorimetry. Finally, these compounds have shown efficacy when dosed orally in multiple acute and chronic prostaglandin and leukotriene dependent in vivo models.

Use of the Biopharmaceutical Classification System in early drug development.

The Biopharmaceutics Classification System (BCS) is not only a useful tool for obtaining waivers for in-vivo bioequivalence studies but also for decision making in the discovery and early development of new drugs. Measurement of solubility and permeability in the discovery/development settings is described. These data can be utilized for the preliminary BCS classification of pipeline compounds. A decision tree is described in the prioritization of salt and polymorph screening studies prior to in vivo studies in animals. For BCS class 1 and 3 compounds, polymorphism is less likely to impact on bioavailability. The polymorph screening study may be postponed after animal studies. The BCS classification can also be used in the design of animal and human formulations. A BCS-based animal formulation development decision tree is presented. A compound is triaged based on a series of decision points into one of the five formulation strategies. Human formulation has different requirements than animal formulation. A comparison between animal and human formulation strategies is presented. In conclusion, for non-BCS 1 compounds, the right-first-time polymorph and formulation selection ensures consistent pharmacokinetic performance and avoids bridging BA/BE studies. It is in line with FDA's initiative to reduce R&D cycle time through quality by design for pharmaceutical products.

Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha.

The synthesis and structure-activity relationship of a series of indole inhibitors of cytosolic phospholipase A2alpha (cPLA2alpha, type IVA phospholipase) are described. Inhibitors of cPLA2alpha are predicted to be efficacious in treating asthma as well as the signs and symptoms of osteoarthritis, rheumatoid arthritis, and pain. The introduction of a benzyl sulfonamide substituent at C2 was found to impart improved potency of these inhibitors, and the SAR of these sulfonamide analogues is disclosed. Compound 123 (Ecopladib) is a sub-micromolar inhibitor of cPLA2alpha in the GLU micelle and rat whole blood assays. Compound 123 displayed oral efficacy in the rat carrageenan air pouch and rat carrageenan-induced paw edema models.