Multimodal Treatment of Patients with Mental Symptom Load: A Pre-Post Comparison.

The Traditional Chinese Medicine (TCM) Hospital in Bad Kötzting, Germany, is treating chronically ill patients, covering a broad range of indications. The aim of this study was to prove the efficacy of a multimodal intervention combining mainstream medicine with TCM treatments on the severity of psychopathological symptoms. Out of 966 patients with chronic psychosomatic disease treated 2017 at the TCM Hospital, we selected 759 patients according to specific criteria and analyzed the outcomes after multimodal intervention. The patients completed a validated questionnaire (International Statistical Classification of Diseases (ICD) Symptom-Rating-(ISR)) at admission, discharge, and follow-up. The most frequent ICD-10 diagnoses were "diseases of the musculoskeletal system and connective tissue" (28.5%), "mental and behavioral disorders" (23.7%), and "diseases of the nervous system" (13.8%). Regarding ISR symptom load, "depressive syndrome" and "anxiety syndrome" were the leading burdens showing remissions of about 40%-60% with moderate (0.588) to strong (1.115) effect sizes (Cohen's d) after treatment. ISR total scores at discharge and follow-up were remarkably lower after intervention (0.64 and 0.75, respectively) compared to 1.02 at admission with moderate to strong effect sizes (0.512-0.815). These findings indicate a clinically relevant relief from mental symptom load after intervention with lasting clinical effects for at least six months.

Mathematical and Experimental Validation of Flux Dialysis Method: An Improved Approach to Measure Unbound Fraction for Compounds with High Protein Binding and Other Challenging Properties.

A flux dialysis method to measure unbound fraction (fu) of compounds with high protein binding and other challenging properties was tested and validated. This method is based on the principle that the initial flux rate of a compound through a size-excluding dialysis membrane is proportional to the product of the compound initial concentration, fu, and unbound dialysis membrane permeability (Pmem). Therefore, fu can be determined from the initial concentration and flux rate, assuming membrane Pmem is known. Compound initial flux rates for 14 compounds were determined by dialyzing human plasma containing compound (donor side) versus compound-free plasma (receiver side) and measuring the rate of compound appearance into the receiver side. Eleven compounds had known fu values obtained from conventional methods (ranging from 0.000013 to 0.22); three compounds (bedaquiline, lapatinib, and pibrentasvir) had previously qualified fu values (e.g., <0.001).Pmem estimated from flux rates and known fu values did not meaningfully differ among the compounds and were consistent with previously published values, indicating that Pmem is a constant for the dialysis membrane. This Pmem constant and the individual compound flux rates were used to calculate fu values. The flux dialysis fu values for the 11 compounds were in good agreement with their reported fu values (all within 2.5-fold; R2 = 0.980), confirming the validity of the method. Furthermore, the flux dialysis method allowed discrete fu to be estimated for the three compounds with previously qualified fu Theoretical and experimental advantages of the flux dialysis method over other dialysis-based protein binding methods are discussed.

Mechanisms and Predictions of Drug-Drug Interactions of the Hepatitis C Virus Three Direct-Acting Antiviral Regimen: Paritaprevir/Ritonavir, Ombitasvir, and Dasabuvir.

To assess drug-drug interaction (DDI) potential for the three direct-acting antiviral (3D) regimen of ombitasvir, dasabuvir, and paritaprevir, in vitro studies profiled drug-metabolizing enzyme and transporter interactions. Using mechanistic static and dynamic models, DDI potential was predicted for CYP3A, CYP2C8, UDP-glucuronosyltransferase (UGT) 1A1, organic anion-transporting polypeptide (OATP) 1B1/1B3, breast cancer resistance protein (BCRP), and P-glycoprotein (P-gp). Perpetrator static model DDI predictions for metabolizing enzymes were within 2-fold of the clinical observations, but additional physiologically based pharmacokinetic modeling was necessary to achieve the same for drug transporters. When perpetrator interactions were assessed, ritonavir was responsible for the strong increase in exposure of sensitive CYP3A substrates, whereas paritaprevir (an OATP1B1/1B3 inhibitor) greatly increased the exposure of sensitive OATP1B1/1B3 substrates. The 3D regimen drugs are UGT1A1 inhibitors and are predicted to moderately increase plasma exposure of sensitive UGT1A1 substrates. Paritaprevir, ritonavir, and dasabuvir are BCRP inhibitors. Victim DDI predictions were qualitatively in line with the clinical observations. Plasma exposures of the 3D regimen were reduced by strong CYP3A inducers (paritaprevir and ritonavir; major CYP3A substrates) but were not affected by strong CYP3A4 inhibitors, since ritonavir (a CYP3A inhibitor) is already present in the regimen. Strong CYP2C8 inhibitors increased plasma exposure of dasabuvir (a major CYP2C8 substrate), OATP1B1/1B3 inhibitors increased plasma exposure of paritaprevir (an OATP1B1/1B3 substrate), and P-gp or BCRP inhibitors (all compounds are substrates of P-gp and/or BCRP) increased plasma exposure of the 3D regimen. Overall, the comprehensive mechanistic assessment of compound disposition along with mechanistic and PBPK approaches to predict victim and perpetrator DDI liability may enable better clinical management of nonstudied drug combinations with the 3D regimen.

East Meets West: Synergy through Diversity.

The TCM hospital Bad Kötzting is historically the first inpatient facility in Germany with an emphasis on Traditional Chinese Medicine (TCM). The clinic's specialty is the multimodal treatment of somatic complaints in conjunction with acute psychological or psychiatric comorbidity. Most patients present with clinical problems of a high degree of chronicity and complexity. Over the past 25 years the treatment concept of the hospital has developed from a strictly TCM approach to a multimodal combination of TCM, psychosomatic medicine, and lifestyle medicine. This article outlines the admission and intake procedures and describes the process of determining the TCM diagnoses and treatment protocols. A typical case study illustrates this process in more details. Then, we present the various components of the psychotherapeutic and psychoeducational programs, including innovative approaches to lifestyle medicine. In conclusion, the treatment program at the TCM hospital Bad Kötzting has developed into a multimodal approach that synergistically intertwines diverse therapies drawn from Eastern and Western traditions, effectively combining the best approaches of both contexts.

Metabolism and Disposition of the Hepatitis C Protease Inhibitor Paritaprevir in Humans.

Paritaprevir (also known as ABT-450), a potent NS3-4A serine protease inhibitor [identified by AbbVie (North Chicago, IL) and Enanta Pharmaceuticals (Watertown, MA)] of the hepatitis C virus (HCV), has been developed in combination with ombitasvir and dasabuvir in a three-direct-acting antiviral agent (DAA) oral regimen for the treatment of patients infected with HCV genotype 1. This article describes the mass balance, metabolism, and disposition of paritaprevir in humans. After the administration of a single 200-mg oral dose of [(14)C]paritaprevir coadministered with 100 mg of ritonavir to four male healthy volunteers, the mean total percentage of the administered radioactive dose recovered was 96.5%, with recovery in individual subjects ranging from 96.0% to 96.9%. Radioactivity derived from [(14)C]paritaprevir was primarily eliminated in feces (87.8% of the dose). Radioactivity recovered in urine accounted for 8.8% of the dose. The biotransformation of paritaprevir in humans involves: 1) P450-mediated oxidation on the olefinic linker, the phenanthridine group, the methylpyrazinyl group, or combinations thereof; and 2) amide hydrolysis at the acyl cyclopropane-sulfonamide moiety and the pyrazine-2-carboxamide moiety. Paritaprevir was the major component in plasma [90.1% of total radioactivity in plasma, AUC from time 0 to 12 hours (AUC0-12hours) pool]. Five minor metabolites were identified in plasma, including the metabolites M2, M29, M3, M13, and M6; none of the metabolites accounted for greater than 10% of the total radioactivity. Paritaprevir was primarily eliminated through the biliary-fecal route followed by microflora-mediated sulfonamide hydrolysis to M29 as a major component in feces (approximately 60% of dose). In summary, the biotransformation and clearance pathways of paritaprevir were characterized, and the structures of metabolites in circulation and excreta were elucidated.

Metabolism and Disposition of Hepatitis C Polymerase Inhibitor Dasabuvir in Humans.

Dasabuvir [also known as ABT-333 or N-(6-(3-(tert-butyl)-5-(2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)-2-methoxyphenyl)naphthalen-2-yl)methanesulfonamide] is a potent non-nucleoside NS protein 5B polymerase inhibitor of the hepatitis C virus (HCV) and is being developed in combination with paritaprevir/ritonavir and ombitasvir in an oral regimen with three direct-acting antivirals for the treatment of patients infected with HCV genotype 1. This article describes the mass balance, metabolism, and disposition of dasabuvir in humans. After administration of a single oral dose of 400-mg [(14)C]dasabuvir (without coadministration of paritaprevir/ritonavir and ombitasvir) to four healthy male volunteers, the mean total percentage of the administered radioactive dose recovered was 96.6%. The recovery from the individual subjects ranged from 90.8% to 103%. Dasabuvir and corresponding metabolites were predominantly eliminated in feces (94.4% of the dose) and minimally through renal excretion (2.2% of the dose). The biotransformation of dasabuvir primarily involves hydroxylation of the tert-butyl group to form active metabolite M1 [N-(6-(5-(2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)-3-(1-hydroxy-2-methylpropan-2-yl)-2-methoxyphenyl)naphthalen-2-yl)methanesulfonamide], followed by glucuronidation and sulfation of M1 and subsequent secondary oxidation. Dasabuvir was the major circulating component (58% of total radioactivity) in plasma, followed by metabolite M1 (21%). Other minor metabolites represented < 10% each of total circulating radioactivity. Dasabuvir was cleared mainly through cytochrome P450-mediated oxidation metabolism to M1. M1 and its glucuronide and sulfate conjugates were primarily eliminated in feces. Subsequent oxidation of M1 to the tert-butyl acid, followed by formation of the corresponding glucuronide conjugate, plays a secondary role in elimination. Cytochrome P450 profiling indicated that dasabuvir was mainly metabolized by CYP2C8, followed by CYP3A4. In summary, the biotransformation pathway and clearance routes of dasabuvir were characterized, and the structures of metabolites in circulation and excreta were elucidated.

Metabolism and Disposition of Pan-Genotypic Inhibitor of Hepatitis C Virus NS5A Ombitasvir in Humans.

Ombitasvir (also known as ABT-267) is a potent inhibitor of hepatitis C virus (HCV) nonstructural protein 5A (NS5A), which has been developed in combination with paritaprevir/ritonavir and dasabuvir in a three direct-acting antiviral oral regimens for the treatment of patients infected with HCV genotype 1. This article describes the mass balance, metabolism, and disposition of ombitasvir in humans without coadministration of paritaprevir/ritonavir and dasabuvir. Following the administration of a single 25-mg oral dose of [(14)C]ombitasvir to four healthy male volunteers, the mean total percentage of the administered radioactive dose recovered was 92.1% over the 192-hour sample collection in the study. The recovery from the individual subjects ranged from 91.4 to 93.1%. Ombitasvir and corresponding metabolites were primarily eliminated in feces (90.2% of dose), mainly as unchanged parent drug (87.8% of dose), but minimally through renal excretion (1.9% of dose). Biotransformation of ombitasvir in human involves enzymatic amide hydrolysis to form M23 (dianiline), which is further metabolized through cytochrome P450-mediated oxidative metabolism (primarily by CYP2C8) at the tert-butyl group to generate oxidative and/or C-desmethyl metabolites. [(14)C]Ombitasvir, M23, M29, M36, and M37 are the main components in plasma, representing about 93% of total plasma radioactivity. The steady-state concentration measurement of ombitasvir metabolites by liquid chromatography-mass spectrometry analysis in human plasma following multiple doses of ombitasvir, in combination with paritaprevir/ritonavir and dasabuvir, confirmed that ombitasvir is the main component (51.9% of all measured drug-related components), whereas M29 (19.9%) and M36 (13.1%) are the major circulating metabolites. In summary, the study characterized ombitasvir metabolites in circulation, the metabolic pathways, and the elimination routes of the drug.

Neural correlates of spatial working memory load in a delayed match-to-sample saccade task.

We propose a new way to identify the neural correlates of memory load in a delayed match-to-sample saccade task with a constant perceptual load. Two conditions were compared with low and high memory loads. In the low-load condition, a rectangular shaped probe defined by its color and orientation was presented centrally. After a delay period, four stimuli were presented peripherally, one in each quadrant. The participants were instructed to saccade to the stimulus that matched the previously viewed sample on both color and orientation. In the high-load condition, the order of stimulus presentation was reversed: first four eccentric stimuli were presented and after a delay the central probe. In the high-load condition, the participant executed a saccade to the remembered location of the stimulus that matched the central probe in color and orientation. The behavioral results indicate that greater working memory load is associated with prolonged saccadic reaction times. A general linear model revealed regions in prefrontal cortex (left anterior insula, right superior and middle frontal gyrus, anterior medial cingulum), and bilaterally along the intraparietal sulcus extending into surrounding areas (precuneus, superior and inferior parietal lobe) that were more activated when participants had to conjointly remember the locations, colors and orientations of four objects (load-4) compared to when they only had to remember the features of a single object (load-1). Specific responses for greater working memory load are focused on regions responsible for feature binding (occipital-temporal cortex) and allocation of attention (anterior insular cortex). Multivariate pattern analysis during the retrieval period of a trial revealed voxel clusters in the ventral visual pathway and the frontal eye fields that correctly classify the target location during the retrieval period of both tasks.

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 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.

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.

Spatiotemporal ICA applied to retinotopic fMRI data.

We use two spatiotemporal Independent Component Analysis algorithms, stJADE and stSOBI, to analyse data from a retinotopic functional magnetic resonance imaging experiment and compare their performance to the analysis of the same data with the spatial ICA done with JADE. This kind of experimental setting has the advantage that the activation in the brain can be estimated fairly easily and therefore can be used as well defined benchmark. We show that stSOBI can outperform sJADE and exhibits quite stable behaviour while stJADE critically depends on the quality of the chosen parameter settings for each subject.

Membrane transporters in drug development.

Membrane transporters can be major determinants of the pharmacokinetic, safety and efficacy profiles of drugs. This presents several key questions for drug development, including which transporters are clinically important in drug absorption and disposition, and which in vitro methods are suitable for studying drug interactions with these transporters. In addition, what criteria should trigger follow-up clinical studies, and which clinical studies should be conducted if needed. In this article, we provide the recommendations of the International Transporter Consortium on these issues, and present decision trees that are intended to help guide clinical studies on the currently recognized most important drug transporter interactions. The recommendations are generally intended to support clinical development and filing of a new drug application. Overall, it is advised that the timing of transporter investigations should be driven by efficacy, safety and clinical trial enrolment questions (for example, exclusion and inclusion criteria), as well as a need for further understanding of the absorption, distribution, metabolism and excretion properties of the drug molecule, and information required for drug labelling.

Absorption, metabolism, and excretion of [14C]vildagliptin, a novel dipeptidyl peptidase 4 inhibitor, in humans.

The absorption, metabolism, and excretion of (1-[[3-hydroxy-1-adamantyl) amino] acetyl]-2-cyano-(S)-pyrrolidine (vildagliptin), an orally active and highly selective dipeptidyl peptidase 4 inhibitor developed for the treatment of type 2 diabetes, were evaluated in four healthy male subjects after a single p.o. 100-mg dose of [(14)C]vildagliptin. Serial blood and complete urine and feces were collected for 168 h postdose. Vildagliptin was rapidly absorbed, and peak plasma concentrations were attained at 1.1 h postdose. The fraction of drug absorbed was calculated to be at least 85.4%. Unchanged drug and a carboxylic acid metabolite (M20.7) were the major circulating components in plasma, accounting for 25.7% (vildagliptin) and 55% (M20.7) of total plasma radioactivity area under the curve. The terminal half-life of vildagliptin was 2.8 h. Complete recovery of the dose was achieved within 7 days, with 85.4% recovered in urine (22.6% unchanged drug) and the remainder in feces (4.54% unchanged drug). Vildagliptin was extensively metabolized via at least four pathways before excretion, with the major metabolite M20.7 resulting from cyano group hydrolysis, which is not mediated by cytochrome P450 (P450) enzymes. Minor metabolites resulted from amide bond hydrolysis (M15.3), glucuronidation (M20.2), or oxidation on the pyrrolidine moiety of vildagliptin (M20.9 and M21.6). The diverse metabolic pathways combined with a lack of significant P450 metabolism (1.6% of the dose) make vildagliptin less susceptible to potential pharmacokinetic interactions with comedications of P450 inhibitors/inducers. Furthermore, as vildagliptin is not a P450 inhibitor, it is unlikely that vildagliptin would affect the metabolic clearance of comedications metabolized by P450 enzymes.

Disposition of vildagliptin, a novel dipeptidyl peptidase 4 inhibitor, in rats and dogs.

The pharmacokinetics, absorption, metabolism, and excretion of vildagliptin, a potent and orally active inhibitor of dipeptidyl peptidase 4, were evaluated in male rats and dogs. Vildagliptin was rapidly absorbed with peak plasma concentrations occurring between 0.5 and 1.5 h. Moderate to high bioavailability was observed in both species (45-100%). The distribution and elimination half-lives of vildagliptin were short: 0.57 h [82% of area under the plasma drug concentration-time curve (AUC)] and 8.8 h in the rat and 0.05 and 0.89 h (87% of AUC) in the dog, respectively. The volume of distribution was 1.6 and 8.6 l/kg in dogs and rats, respectively, indicating moderate to high tissue distribution. The plasma clearance of vildagliptin was relatively high for the rat (2.9 l/h/kg) and dog (1.3 l/h/kg) compared with their hepatic blood flow. The major circulating components in plasma after an intravenous or oral dose were the parent compound (rat and dog), a carboxylic acid metabolite from the hydrolysis of the amide bond M15.3 (dog), and a carboxylic acid metabolite from the hydrolysis of the cyano moiety M20.7 (rat and dog). After intravenous dosing, urinary excretion of radioactivity (47.6-72.4%) was the major route of elimination for rats and dogs as 18.9 to 21.3% of the dose was excreted into urine as unchanged parent drug. The recovery was good in both species (81-100% of the dose). Vildagliptin was mainly metabolized before excretion in both species. Similar to plasma, the most predominant metabolite in excreta was M20.7 in rats and dogs, and another major metabolite in dogs was M15.3.

Use of classification regression tree in predicting oral absorption in humans.

The purpose of this study is to explore the use of classification regression trees (CART) in predicting, in the dose-independent range, the fraction dose absorbed in humans. Since the results from clinical formulations in humans were used for training the model, a hypothetical state of drug molecules already dissolved in the intestinal fluid was adopted. Therefore, the molecular attributes affecting dissolution were not considered in the model. As a result, the model projects the highest achievable fraction dose absorbed, providing a reference point for manipulating the formulations or solid states to optimize oral clinical efficacy. A set of approximately 1260 structures and their human oral pharmacokinetic data, including bioavailability and/or absorption and/or radio-labeled studies, were used, with 899 compounds as the training set and 362 the test set. The numerical range of the fraction dose absorbed, 0 to 1, was divided into 6 classes with each class having a size of approximately 0.16. A set of 28 structural descriptors was used for modeling oral absorption without considering active transport. Then, a separate branch was created for modeling oral absorption involving active transport. The AAE of the training set was 0.12 and those of five test sets ranged from 0.17 to 0.2. In terms of classification, two test sets of unpublished, proprietary compounds showed 79% to 86% prediction when the predicted values fallen within +/- one class of real values were considered predicted. Overall, the computational errors from all the test sets of diverse structures were similar and reasonably acceptable. As compared to artificial membranes for ranking drug absorption potential, prediction by the CART model is considered fast and reasonably accurate for accelerating drug discovery. One can not only improve continuously the accuracy of CART computations by expanding the chemical space of the training set but also calculate the statistical errors associated with individual decision paths resulting from the training set to determine whether to accept individual computations of any test sets.

The conduct of in vitro and in vivo drug-drug interaction studies: a Pharmaceutical Research and Manufacturers of America (PhRMA) perspective.

Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches, to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (P450) probe substrates, inhibitors and inducers and for the development of classification systems to improve the communication of risk to health care providers and to patients. While existing guidances cover mainly P450-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently, and should also be addressed. This article was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.

The conduct of in vitro and in vivo drug-drug interaction studies: a PhRMA perspective.

Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (CYP) probe substrates, inhibitors, and inducers and for the development of classification systems to improve the communication of risk to health care providers and patients. While existing guidances cover mainly CYP-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently and should also be addressed. This paper was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.