Preclinical Bioavailability Strategy for Decisions on Clinical Drug Formulation Development: An In Depth Analysis.

The aim of the presented retrospective analysis was to verify whether a previously proposed Janssen Biopharmaceutical Classification System (BCS)-like decision tree, based on preclinical bioavailability data of a solution and suspension formulation, would facilitate informed decision making on the clinical formulation development strategy. In addition, the predictive value of (in vitro) selection criteria, such as solubility, human permeability, and/or a clinical dose number (Do), were evaluated, potentially reducing additional supporting formulation bioavailability studies in animals. The absolute ( Fabs,sol) and relative ( Frel, susp/sol) bioavailability of an oral solution and suspension, respectively, in rat or dog and the anticipated BCS classification were analyzed for 89 Janssen compounds with 28 of these having Frel,susp/sol and Fabs,sol in both rat and dog at doses around 10 and 5 mg/kg, respectively. The bioavailability outcomes in the dog aligned well with a BCS-like classification based upon the solubility of the active pharmaceutical ingredient (API) in biorelevant media, while the alignment was less clear for the bioavailability data in the rat. A retrospective analysis on the clinically tested formulations for a set of 12 Janssen compounds confirmed that the previously proposed animal bioavailability-based decision tree facilitated decisions on the oral formulation type, with the dog as the most discriminative species. Furthermore, the analysis showed that based on a Do for a standard human dose of 100 mg in aqueous and/or biorelevant media, a similar formulation type would have been selected compared to the one suggested by the animal data. However, the concept of a Do did not distinguish between solubility enhancing or enabling formulations and does not consider the API permeability, and hence, it produces the risk of slow and potentially incomplete oral absorption of an API with poor intestinal permeability. In cases where clinical dose estimations are available early in development, the preclinical bioavailability studies and dose number calculations, used to guide formulation selection, may be performed at more relevant doses instead of the proposed standard human dose. It should be noted, however, that unlike in late development, there is uncertainty on the clinical dose estimated in the early clinical phases because that dose is usually only based on in vitro and/or in vivo animal pharmacology models, or early clinical biomarker information. Therefore, formulation strategies may be adjusted based on emerging data supporting clinical doses. In summary, combined early information on in vitro-assessed API solubility and permeability, preclinical suspension/solution bioavailability data in relation to the intravenous clearance, and metabolic pathways of the API can strengthen formulation decisions. However, these data may not always fully distinguish between conventional (e.g., to be taken with food), enhancing, and enabling formulations. Therefore, to avoid overinvestment in complex and expensive enabling technologies, it is useful to evaluate a conventional and solubility (and/or permeability) enhancing formulation under fasted and fed conditions, as part of a first-in-human study or in a subsequent early human bioavailability study, for compounds with high Do, a low animal Frel,susp/sol, or low Fabs,sol caused by precipitation of the solubilized API.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results.

Orally administered drugs are subject to a number of barriers impacting bioavailability (Foral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, Foral and relative AUC (Frel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes.

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. Foral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.

IMI - oral biopharmaceutics tools project - evaluation of bottom-up PBPK prediction success part 1: Characterisation of the OrBiTo database of compounds.

Predicting oral bioavailability (Foral) is of importance for estimating systemic exposure of orally administered drugs. Physiologically-based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large-scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large-scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40-4.58), human blood-to-plasma ratio of 0.62 (0.57-0.71), and fraction unbound in plasma of 0.05 (0.01-0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9L/h (interquartile range: 11.6-43.6L/h; n=23), volume of distribution was 80.8L (54.5-239L; n=23). The majority of oral formulations were immediate release (IR: 87.6%). Human Foral displayed a median of 0.415 (0.203-0.724; n=22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large-scale evaluation of the PBPK approach to predicting oral biopharmaceutics.

Strategies for Determining Correct Cytochrome P450 Contributions in Hepatic Clearance Predictions: In Vitro-In Vivo Extrapolation as Modelling Approach and Tramadol as Proof-of Concept Compound.

BACKGROUND AND OBJECTIVE: Although the measurement of cytochrome P450 (CYP) contributions in metabolism assays is straightforward, determination of actual in vivo contributions might be challenging. How representative are in vitro for in vivo CYP contributions? This article proposes an improved strategy for the determination of in vivo CYP enzyme-specific metabolic contributions, based on in vitro data, using an in vitro-in vivo extrapolation (IVIVE) approach. Approaches are exemplified using tramadol as model compound, and CYP2D6 and CYP3A4 as involved enzymes. METHODS: Metabolism data for tramadol and for the probe substrates midazolam (CYP3A4) and dextromethorphan (CYP2D6) were gathered in human liver microsomes (HLM) and recombinant human enzyme systems (rhCYP). From these probe substrates, an activity-adjustment factor (AAF) was calculated per CYP enzyme, for the determination of correct hepatic clearance contributions. As a reference, tramadol CYP contributions were scaled-back from in vivo data (retrograde approach) and were compared with the ones derived in vitro. In this view, the AAF is an enzyme-specific factor, calculated from reference probe activity measurements in vitro and in vivo, that allows appropriate scaling of a test drug's in vitro activity to the 'healthy volunteer' population level. Calculation of an AAF, thus accounts for any 'experimental' or 'batch-specific' activity difference between in vitro HLM and in vivo derived activity. RESULTS: In this specific HLM batch, for CYP3A4 and CYP2D6, an AAF of 0.91 and 1.97 was calculated, respectively. This implies that, in this batch, the in vitro CYP3A4 activity is 1.10-fold higher and the CYP2D6 activity 1.97-fold lower, compared to in vivo derived CYP activities. CONCLUSION: This study shows that, in cases where the HLM pool does not represent the typical mean population CYP activities, AAF correction of in vitro metabolism data, optimizes CYP contributions in the prediction of hepatic clearance. Therefore, in vitro parameters for any test compound, obtained in a particular batch, should be corrected with the AAF for the respective enzymes. In the current study, especially the CYP2D6 contribution was found, to better reflect the average in vivo situation. It is recommended that this novel approach is further evaluated using a broader range of compounds.

Use of physiologically relevant biopharmaceutics tools within the pharmaceutical industry and in regulatory sciences: Where are we now and what are the gaps?

Regulatory interactions are an important part of the drug development and licensing process. A survey on the use of biopharmaceutical tools for regulatory purposes has been carried out within the industry community of the EU project OrBiTo within Innovative Medicines Initiative (IMI). The aim was to capture current practice and experience in using in vitro and in silico biopharmaceutics tools at various stages of development, what barriers exist or are perceived, and to understand the current gaps in regulatory biopharmaceutics. The survey indicated that biorelevant dissolution testing and physiologically based modelling and simulation are widely applied throughout development to address a number of biopharmaceutics issues. However, data from these in vitro and in silico predictive biopharmaceutics tools are submitted to regulatory authorities far less often than they are used for internal risk assessment and decision making. This may prevent regulators from becoming familiar with these tools and how they are applied in industry, and limits the opportunities for biopharmaceutics scientists working in industry to understand the acceptability of these tools in the regulatory environment. It is anticipated that the advanced biopharmaceutics tools and understanding delivered in the next years by OrBiTo and other initiatives in the area of predictive tools will also be of value in the regulatory setting, and provide a basis for more informed and confident biopharmaceutics risk assessment and regulatory decision making. To enable the regulatory potential of predictive biopharmaceutics tools to be realized, further scientific dialogue is needed between industry, regulators and scientists in academia, and more examples need to be published to demonstrate the applicability of these tools.

Single-Dose Pharmacokinetic Study of Tramadol Extended-Release Tablets in Children and Adolescents.

Combined analyses from 2 open-label, phase-1 studies-the pharmacokinetic profile of tramadol and its metabolite (M1) following a single oral dose of tramadol extended release (ER) (25 to 100 mg) in children (7 to 11 years old; study 1: n = 37) and adolescents (12 to 17 years old; study 2: n = 38) with painful conditions-were historically compared with that of healthy adults following similar dosing. The dose-normalized area under the curve (DN AUC0-24h ) and maximum concentration (DN Cmax ) of tramadol and of M1 in children and in adolescents were lower than those in adults (children vs adults: tramadol, DN AUC0-24h 82.19%; DN Cmax 80.38%, P = .0031; M1, DN AUC0-24h 51.19%, DN Cmax 52.68%, P < .0001; adolescents vs adults: tramadol, DN AUC0-24h 89.56%, DN Cmax 84.01%; M1, DN AUC0-24h 85.28%, DN Cmax 83.03%, P = .0004). The arithmetic mean terminal elimination t1/2 of tramadol in children and adolescents was comparable to that in adults (children 8.4 hours; adolescents 8.5 hours; adults 7.9 hours). The most frequently reported (≥5% of participants) treatment-emergent adverse events in children included headache, upper abdominal pain and constipation, and in adolescents were headache, nausea, dizziness, and stomach discomfort. Multiple factors may have contributed to these observations, including a higher proportion of children (56%) who may have a lower activity of CYP2D6, resulting in reduced clearance of tramadol.

Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation.

This paper focuses on the retrospective evaluation of physiologically based pharmacokinetic (PBPK) techniques used to mechanistically predict clearance throughout pediatric life. An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions. Subsequently, the model was evaluated for mechanistic prediction of total, CYP2D6-related, and renal clearance predictions in very early life. In two in vitro pediatric human liver microsomal (HLM) batches (1 and 3 months), O-desmethyltramadol and N-desmethyltramadol formation rates were compared with CYP2D6 and CYP3A4 activity, respectively. O-desmethyltramadol formation was mediated only by CYP2D6, while N-desmethyltramadol was mediated in part by CYP3A4. Additionally, the clearance maturation of the PBPK model predictions was compared to two in vivo maturation models (Hill and exponential) based on plasma concentration data, and to clearance estimations from a WinNonlin® fit of plasma concentration and urinary excretion data. Maturation of renal and CYP2D6 clearance is captured well in the PBPK model predictions, but total tramadol clearance is underpredicted. The most pronounced underprediction of total and CYP2D6-mediated clearance was observed in the age range of 2-13 years. In conclusion, the PBPK technique showed to be a powerful mechanistic tool capable of predicting maturation of CYP2D6 and renal tramadol clearance in early infancy, although some underprediction occurs between 2 and 13 years for total and CYP2D6-mediated tramadol clearance.

Physiology-based IVIVE predictions of tramadol from in vitro metabolism data.

PURPOSE: To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (Simcyp®). METHODS: Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLintH) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. RESULTS: Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. CONCLUSION: IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults.

Molecular properties determining unbound intracellular and extracellular brain exposure of CNS drug candidates.

In the present work we sought to gain a mechanistic understanding of the physicochemical properties that influence the transport of unbound drug across the blood-brain barrier (BBB) as well as the intra- and extracellular drug exposure in the brain. Interpretable molecular descriptors that significantly contribute to the three key neuropharmacokinetic properties related to BBB drug transport (Kp,uu,brain), intracellular accumulation (Kp,uu,cell), and binding and distribution in the brain (Vu,brain) for a set of 40 compounds were identified using partial least-squares (PLS) analysis. The tailoring of drug properties for improved brain exposure includes decreasing the polarity and/or hydrogen bonding capacity. The design of CNS drug candidates with intracellular targets may benefit from an increase in basicity and/or the number of hydrogen bond donors. Applying this knowledge in drug discovery chemistry programs will allow designing compounds with more desirable CNS pharmacokinetic properties.

Mechanistic understanding of brain drug disposition to optimize the selection of potential neurotherapeutics in drug discovery.

PURPOSE: The current project was undertaken with the aim to propose and test an in-depth integrative analysis of neuropharmacokinetic (neuroPK) properties of new chemical entities (NCEs), thereby optimizing the routine of evaluation and selection of novel neurotherapeutics. METHODS: Forty compounds covering a wide range of physicochemical properties and various CNS targets were investigated. The combinatory mapping approach was used for the assessment of the extent of blood-brain and cellular barriers transport via estimation of unbound-compound brain (Kp,uu,brain) and cell (Kp,uu,cell) partitioning coefficients. Intra-brain distribution was evaluated using the brain slice method. Intra- and sub-cellular distribution was estimated via calculation of unbound-drug cytosolic and lysosomal partitioning coefficients. RESULTS: Assessment of Kp,uu,brain revealed extensive variability in the brain penetration properties across compounds, with a prevalence of compounds actively effluxed at the blood-brain barrier. Kp,uu,cell was valuable for identification of compounds with a tendency to accumulate intracellularly. Prediction of cytosolic and lysosomal partitioning provided insight into the subcellular accumulation. Integration of the neuroPK parameters with pharmacodynamic readouts demonstrated the value of the proposed approach in the evaluation of target engagement and NCE selection. CONCLUSIONS: With the rather easily-performed combinatory mapping approach, it was possible to provide quantitative information supporting the decision making in the drug discovery setting.

The successes and failures of physiologically based pharmacokinetic modeling: there is room for improvement.

From the year 2000 onwards, physiologically based pharmacokinetic (PBPK) models in the field of drug research and development have been increasingly used. This proliferation of applications was prompted by the availability of new data and computational approaches required for the parameterization of PBPK models, as well as the availability of commercial software platforms. PBPK approaches have been used to predict drug pharmacokinetics in humans based on nonclinical data, the potential for drug-drug interactions and the expected changes in the pharmacokinetics in case of different physiopathological conditions. In this respect, PBPK is also assuming a more important role in regulatory submissions. Although PBPK methodologies are not perfect yet, their continuous and consistent application is providing a more profound understanding of the determinants of the drug absorption and disposition of new and candidate drugs. We are confident that, with increased use, PBPK methodologies will gradually improve in their predictive capabilities.

Towards a better prediction of peak concentration, volume of distribution and half-life after oral drug administration in man, using allometry.

BACKGROUND: It is imperative that new drugs demonstrate adequate pharmacokinetic properties, allowing an optimal safety margin and convenient dosing regimens in clinical practice, which then lead to better patient compliance. Such pharmacokinetic properties include suitable peak (maximum) plasma drug concentration (C(max)), area under the plasma concentration-time curve (AUC) and a suitable half-life (t(½)). The C(max) and t(½) following oral drug administration are functions of the oral clearance (CL/F) and apparent volume of distribution during the terminal phase by the oral route (V(z)/F), each of which may be predicted and combined to estimate C(max) and t(½). Allometric scaling is a widely used methodology in the pharmaceutical industry to predict human pharmacokinetic parameters such as clearance and volume of distribution. In our previous published work, we have evaluated the use of allometry for prediction of CL/F and AUC. In this paper we describe the evaluation of different allometric scaling approaches for the prediction of C(max), V(z)/F and t(½) after oral drug administration in man. METHODS: Twenty-nine compounds developed at Janssen Research and Development (a division of Janssen Pharmaceutica NV), covering a wide range of physicochemical and pharmacokinetic properties, were selected. The C(max) following oral dosing of a compound was predicted using (i) simple allometry alone; (ii) simple allometry along with correction factors such as plasma protein binding (PPB), maximum life-span potential or brain weight (reverse rule of exponents, unbound C(max) approach); and (iii) an indirect approach using allometrically predicted CL/F and V(z)/F and absorption rate constant (k(a)). The k(a) was estimated from (i) in vivo pharmacokinetic experiments in preclinical species; and (ii) predicted effective permeability in man (P(eff)), using a Caco-2 permeability assay. The V(z)/F was predicted using allometric scaling with or without PPB correction. The t(½) was estimated from the allometrically predicted parameters CL/F and V(z)/F. Predictions were deemed adequate when errors were within a 2-fold range. RESULTS: C(max) and t(½) could be predicted within a 2-fold error range for 59% and 66% of the tested compounds, respectively, using allometrically predicted CL/F and V(z)/F. The best predictions for C(max) were obtained when k(a) values were calculated from the Caco-2 permeability assay. The V(z)/F was predicted within a 2-fold error range for 72% of compounds when PPB correction was applied as the correction factor for scaling. CONCLUSIONS: We conclude that (i) C(max) and t(½) are best predicted by indirect scaling approaches (using allometrically predicted CL/F and V(z)/F and accounting for k(a) derived from permeability assay); and (ii) the PPB is an important correction factor for the prediction of V(z)/F by using allometric scaling. Furthermore, additional work is warranted to understand the mechanisms governing the processes underlying determination of C(max) so that the empirical approaches can be fine-tuned further.

Variability and impact on design of bioequivalence studies.

In 2008, the European Agency for the Evaluation of Medicinal Products released a draft guidance on the investigation of bioequivalence for immediate release dosage forms with systemic action to replace the former guidance of a decade ago. Revisions of the regulatory guidance are based upon many questions over the past years and sometimes continuing scientific discussions on the use of the most suitable statistical analysis methods and study designs, particularly for drugs and drug products with high within-subject variability. Although high within-subject variability is usually associated with a coefficient of variation of 30% or more, new approaches are available in the literature to allow a gradual increase and a levelling off of the bioequivalence limits to some maximum wider values (e.g. 75-133%), dependent on the increase in the within-subject variability. The two-way, cross-over single dose study measuring parent drug is still the design of first choice. A partial replicate design with repeating the reference product and scaling the bioequivalence for the reference variability are proposed for drugs with high within-subject variability. In case of high variability, more regulatory authorities may accept a two-stage or group-sequential bioequivalence design using appropriately adjusted statistical analysis. This review also considers the mechanisms why drugs and drug products may exhibit large variability. The physiological complexity of the gastrointestinal tract and the interaction with the physicochemical properties of drug substances may contribute to the variation in plasma drug concentration-time profiles of drugs and drug products and to variability between and within subjects. A review of submitted bioequivalence studies at the Food and Drug Administration's Office of Generic Drugs over the period 2003-2005 indicated that extensive pre-systemic metabolism of the drug substance was the most important explanation for consistently high variability drugs, rather than a formulation factor. These scientific efforts are expected to further lead to revisions of earlier regulatory guidance in other regions as is the current situation in Europe.

Physiologically-based PK/PD modelling of therapeutic macromolecules.

Therapeutic proteins are a diverse class of drugs consisting of naturally occurring or modified proteins, and due to their size and physico-chemical properties, they can pose challenges for the pharmacokinetic and pharmacodynamic studies. Physiologically-based pharmacokinetics (PBPK) modelling has been effective for early in silico prediction of pharmacokinetic properties of new drugs. The aim of the present workshop was to discuss the feasibility of PBPK modelling of macromolecules. The classical PBPK approach was discussed with a presentation of the successful example of PBPK modelling of cyclosporine A. PBPK model was performed with transport of the cyclosporine across cell membranes, affinity to plasma proteins and active membrane transporters included to describe drug transport between physiological compartments. For macromolecules, complex PBPK modelling or permeability-limited and/or target-mediated distribution was discussed. It was generally agreed that PBPK modelling was feasible and desirable. The role of the lymphatic system should be considered when absorption after extravascular administration is modelled. Target-mediated drug disposition was regarded as an important feature for generation of PK models. Complex PK-models may not be necessary when a limited number of organs are affected. More mechanistic PK/PD models will be relevant when adverse events/toxicity are included in the PK/PD modelling.

Including information on the therapeutic window in bioequivalence acceptance.

PURPOSE: A novel bioequivalence limit is proposed taking into account the therapeutic window. METHODS: The therapeutic range is introduced as the ratios maximum tolerated dose/therapeutic dose (MTD/D) and the therapeutic dose/lowest effective dose. The performance of the new acceptance range was compared with the methods of Schuirmann and Karalis. The method was retrospectively applied to data of three drugs with a narrow therapeutic window (phenytoin, theophylline and digoxin). RESULTS: Simulations and examples show that the resulting bioequivalence limits are (1) narrow for narrow-index drugs, (2) expanded for highly variable drugs with a wide therapeutic window and (3) similar to the classical limits for less variable drugs with a wide therapeutic range. CONCLUSIONS: The approach has the desirable property of resulting in a more narrow acceptance range for doses near the boundaries of the therapeutic window and a wider acceptance range for products with a broad therapeutic window.

Bioavailability and bioequivalence: focus on physiological factors and variability.

This is a summary report of the EUFEPS & COST B25 conference on Bioavailability and Bioequivalence which focused on physiological factors and variability. This conference was held at The Royal Olympic Hotel in the centre of Athens (Greece) during the 1-2 of October in 2007. The issues discussed in the conference involved physiological factors affecting drug absorption, the role of pre-systemic effects on bioavailability (BA), the impact of variability in bioequivalence (BE) studies, and a final closing panel session on unresolved issues in BA/BE regulations. Several important aspects of drug absorption were highlighted. It was presented how the complexity of gastrointestinal (GI) physiology and the site dependent absorption can impact on drug BA. Similarly, the effects of food and formulation were also studied. The second session focused on integrating the complexities of GI into modeling the inter-individual variability of absorption and the prediction of first-pass metabolism from in-vitro data. The necessity to measure metabolites, the value of Biopharmaceutical Classification System (BCS), and the more recently proposed Biopharmaceutical Drug Disposition Classification System (BDDCS) were assessed as well. This session closed with presentations of pharmacokinetic software delegates. In the second day of the conference, the problem of high intra-subject variability in BE studies was analyzed. Study design considerations, the use of multiple-dose studies and the role of statistics in BE were also highlighted. Finally, the current thinking of regulatory authorities (EMEA and US-FDA) was presented. The conference closed with a last session on unresolved issues in the regulatory level.

Predicting oral clearance in humans: how close can we get with allometry?

BACKGROUND: Oral clearance (CL/F) is an important pharmacokinetic parameter and plays an important role in the selection of a safe and tolerable dose for first-in-human studies. Throughout the pharmaceutical industry, many drugs are administered via the oral route; however, there are only a handful of published scaling studies for the prediction of oral pharmacokinetic parameters. METHODS: We evaluated the predictive performances of four different allometric approaches -- simple allometry (SA), the rule of exponents, the unbound CL/F approach, and the unbound fraction corrected intercept method (FCIM) -- for the prediction of human CL/F and the oral area under the plasma concentration-time curve (AUC). Twenty-four compounds developed at Johnson and Johnson Pharmaceutical Research and Development, covering a wide range of physicochemical and pharmacokinetic properties, were selected. The CL/F was predicted using these approaches, and the oral AUC was then estimated using the predicted CL/F. RESULTS: The results of this study indicated that the most successful predictions of CL/F and the oral AUC were obtained using the unbound CL/F approach in combination with the maximum lifespan potential or the brain weight as correction factors based on the rule of exponents. We also observed that the unbound CL/F approach gave better predictions when the exponent of SA was between 0.5 and 1.2. However, the FCIM seemed to be the method of choice when the exponent of SA was <0.50 or >1.2. CONCLUSIONS: Overall, we were able to predict CL/F and the oral AUC within 2-fold of the observed value for 79% and 83% of the compounds, respectively, by selecting the allometric approaches based on the exponents of SA.

Modelling and simulation in the development and use of anti-cancer agents: an underused tool?

To help identify the role of modelling and simulation in the development of anti-cancer agents, their main advantages and the obstacles to their rational use, an expert meeting was organized by COST B15. This manuscript presents a synthesis of views expressed at that meeting and indicates future directions. The manuscript also shows some examples where modelling and simulation have proven to be of relevant value in the drug development process for anti-cancer agents.

Galantamine population pharmacokinetics in patients with Alzheimer's disease: modeling and simulations.

Galantamine is a reversible, competitive inhibitor of acetylcholinesterase and an allosteric modulator of nicotinic acetylcholine receptors. It is cleared by renal and hepatic mechanisms, including metabolism by the CYP 450 2D6 and 3A4 isoenzymes. The authors estimated the population pharmacokinetics of galantamine using nonlinear mixed-effects modeling as implemented in NONMEM software. Data from 15 clinical studies (1089 individuals, 7480 concentration measurements in total) were used to examine the effect of body size, demographic characteristics, and concomitant disease status on galantamine pharmacokinetic parameters. Galantamine clearance was shown to decrease with age and increase with body weight and creatinine clearance of individuals. Median clearance in male and female patients with Alzheimer's disease (AD) was 14.8 and 12.4 L/h, respectively. The dissimilarity was related to the body weight difference, not to the real gender effect. Metabolic clearance was reduced by 60% in patients with moderate or severe hepatic dysfunction (Pugh score 7 or higher). Simulations were performed to assess the impact of hepatic impairment and renal insufficiency on peak plasma concentration of galantamine. Simulations confirmed the need for slower dose titration in patients with hepatic impairment: 4 mg daily during 1 week followed by 4, 8, and 12 mg bid, with each dose level during 1 week compared to the standard titration scheme 4-8-12-16 mg bid. However, no significant differences between plasma levels in AD patients with and without severe renal insufficiency were found. CYP 450 2D6 genotype also influenced galantamine clearance but not to the extent that dose adjustment is required.