PK/PD and Bioanalytical Considerations of AAV-Based Gene Therapies: an IQ Consortium Industry Position Paper.

Interest and efforts to use recombinant adeno-associated viruses (AAV) as gene therapy delivery tools to treat disease have grown exponentially. However, gaps in understanding of the pharmacokinetics/pharmacodynamics (PK/PD) and disposition of this modality exist. This position paper comes from the Novel Modalities Working Group (WG), part of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ). The pan-industry WG effort focuses on the nonclinical PK and clinical pharmacology aspects of AAV gene therapy and related bioanalytical considerations.Traditional PK concepts are generally not applicable to AAV-based therapies due to the inherent complexity of a transgene-carrying viral vector, and the multiple steps and analytes involved in cell transduction and transgene-derived protein expression. Therefore, we explain PK concepts of biodistribution of AAV-based therapies and place key terminologies related to drug exposure and PD in the proper context. Factors affecting biodistribution are presented in detail, and guidelines are provided to design nonclinical studies to enable a stage-gated progression to Phase 1 testing. The nonclinical and clinical utility of transgene DNA, mRNA, and protein analytes are discussed with bioanalytical strategies to measure these analytes. The pros and cons of qPCR vs. ddPCR technologies for DNA/RNA measurement and qualitative vs. quantitative methods for transgene-derived protein are also presented. Last, best practices and recommendations for use of clinical and nonclinical data to project human dose and response are discussed. Together, the manuscript provides a holistic framework to discuss evolving concepts of PK/PD modeling, bioanalytical technologies, and clinical dose selection in gene therapy.

Serum albumin binding knob domains engineered within a VH framework III bispecific antibody format and as chimeric peptides.

Background: Serum albumin binding is an established mechanism to extend the serum half-life of antibody fragments and peptides. The cysteine rich knob domains, isolated from bovine antibody ultralong CDRH3, are the smallest single chain antibody fragments described to date and versatile tools for protein engineering. Methods: Here, we used phage display of bovine immune material to derive knob domains against human and rodent serum albumins. These were used to engineer bispecific Fab fragments, by using the framework III loop as a site for knob domain insertion. Results: By this route, neutralisation of the canonical antigen (TNFα) was retained but extended pharmacokinetics in-vivo were achieved through albumin binding. Structural characterisation revealed correct folding of the knob domain and identified broadly common but non-cross-reactive epitopes. Additionally, we show that these albumin binding knob domains can be chemically synthesised to achieve dual IL-17A neutralisation and albumin binding in a single chemical entity. Conclusions: This study enables antibody and chemical engineering from bovine immune material, via an accessible discovery platform.

TRYBE®: an Fc-free antibody format with three monovalent targeting arms engineered for long in vivo half-life.

TrYbe® is an Fc-free therapeutic antibody format, capable of engaging up to three targets simultaneously, with long in vivo half-life conferred by albumin binding. This format is shown by small-angle X-ray scattering to be conformationally flexible with favorable 'reach' properties. We demonstrate the format's broad functionality by co-targeting of soluble and cell surface antigens. The benefit of monovalent target binding is illustrated by the lack of formation of large immune complexes when co-targeting multivalent antigens. TrYbes® are manufactured using standard mammalian cell culture and protein A affinity capture processes. TrYbes® have been formulated at high concentrations and have favorable drug-like properties, including stability, solubility, and low viscosity. The unique functionality and inherent developability of the TrYbe® makes it a promising multi-specific antibody fragment format for antibody therapy.

Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper.

Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.

Use of selective substrates and inhibitors to rapidly characterise batches of cryopreserved primary human hepatocytes for assessment of active uptake liability in drug discovery and development.

The use of hepatocytes to predict human hepatic metabolic clearance is the gold standard approach. However whilst enzymes are well characterised, knowledge gaps remain for transporters. Furthermore, methods to study specific transporter involvement are often complicated by overlapping substrate specificity. Selective substrates and inhibitors would aid investigations into clinically relevant pharmacokinetic effects. However, to date no consensus has been reached.This work defines selective hepatic uptake transporter substrates and inhibitors for the six main human hepatocyte transporters (OATP1B1, OATP1B3, OATP2B1, NTCP, OAT2 & OCT1), and demonstrates their use to rapidly characterise batches of human hepatocytes for uptake transporter activity. Hepatic uptake was determined across a range of substrate concentrations, allowing the definition of kinetic parameters and hence active and passive components. Systematic investigations identified a specific substrate and inhibitor for each transporter, with no overlap between the specificity of substrate and inhibitor for any given transporter.Early characterisation of compound interactions with uptake transporters will aid in early risk assessment and chemistry design. Hence, this work further highlights the feasibility of a refined methodology for rapid compound characterisation for the application of static and dynamic models, for early clinical risk assessment and guidance for the clinical development plan.

Designing Out PXR Activity on Drug Discovery Projects: A Review of Structure-Based Methods, Empirical and Computational Approaches.

This perspective discusses the role of pregnane xenobiotic receptor (PXR) in drug discovery and the impact of its activation on CYP3A4 induction. The use of structural biology to reduce PXR activity on drug discovery projects has become more common in recent years. Analysis of this work highlights several important molecular interactions, and the resultant structural modifications to reduce PXR activity are summarized. The computational approaches undertaken to support the design of new drugs devoid of PXR activation potential are also discussed. Finally, the SAR of empirical design strategies to reduce PXR activity is reviewed, and the key SAR transformations are discussed and summarized. In conclusion, this perspective demonstrates that PXR activity can be greatly diminished or negated on active drug discovery projects with the knowledge now available. This perspective should be useful to anyone who seeks to reduce PXR activity on a drug discovery project.

PBPK Model of Coproporphyrin I: Evaluation of the Impact of SLCO1B1 Genotype, Ethnicity, and Sex on its Inter-Individual Variability.

Coproporphyrin I (CPI) is an endogenous biomarker of OATP1B activity and associated drug-drug interactions. In this study, a minimal physiologically-based pharmacokinetic model was developed to investigate the impact of OATP1B1 genotype (c.521T>C), ethnicity, and sex on CPI pharmacokinetics and interindividual variability in its baseline. The model implemented mechanistic descriptions of CPI hepatic transport between liver blood and liver tissue and renal excretion. Key model parameters (e.g., endogenous CPI synthesis rate, and CPI hepatic uptake clearance) were estimated by fitting the model simultaneously to three independent CPI clinical datasets (plasma and urine data) obtained from white (n = 16, men and women) and Asian-Indian (n = 26, all men) subjects, with c.521 variants (TT, TC, and CC). The optimized CPI model successfully described the observed data using c.521T>C genotype, ethnicity, and sex as covariates. CPI hepatic active was 79% lower in 521CC relative to the wild type and 42% lower in Asian-Indians relative to white subjects, whereas CPI synthesis was 23% higher in male relative to female subjects. Parameter sensitivity analysis showed marginal impact of the assumption of CPI synthesis site (blood or liver), resulting in comparable recovery of plasma and urine CPI data. Lower magnitude of CPI-drug interaction was simulated in 521CC subjects, suggesting the risk of underestimation of CPI-drug interaction without prior OATP1B1 genotyping. The CPI model incorporates key covariates contributing to interindividual variability in its baseline and highlights the utility of the CPI modeling to facilitate the design of prospective clinical studies to maximize the sensitivity of this biomarker.

A mechanistic modelling approach for the determination of the mechanisms of inhibition by cyclosporine on the uptake and metabolism of atorvastatin in rat hepatocytes using a high throughput uptake method.

Determine the inhibition mechanism through which cyclosporine inhibits the uptake and metabolism of atorvastatin in fresh rat hepatocytes using mechanistic models applied to data generated using a high throughput oil spin method.Atorvastatin was incubated in fresh rat hepatocytes (0.05-150 nmol/ml) with or without 20 min pre-incubation with 10 nmol/ml cyclosporine and sampled over 0.25-60 min using a high throughput oil spin method. Micro-rate constant and macro-rate constant mechanistic models were ranked based on goodness of fit values.The best fitting model to the data was a micro-rate constant mechanistic model including non-competitive inhibition of uptake and competitive inhibition of metabolism by cyclosporine (Model 2). The association rate constant for atorvastatin was 150-fold greater than the dissociation rate constant and 10-fold greater than the translocation into the cell. The association and dissociation rate constants for cyclosporine were 7-fold smaller and 10-fold greater, respectively, than atorvastatin. The simulated atorvastatin-transporter-cyclosporine complex derived using the micro-rate constant parameter estimates increased in line with the incubation concentration of atorvastatin.The increased amount of data generated with the high throughput oil spin method, combined with a micro-rate constant mechanistic model helps to explain the inhibition of uptake by cyclosporine following pre-incubation.

Comprehensive Evaluation of the Utility of 20 Endogenous Molecules as Biomarkers of OATP1B Inhibition Compared with Rosuvastatin and Coproporphyrin I.

Endogenous biomarkers can be clinically relevant tools for the assessment of transporter function in vivo and corresponding drug-drug interactions (DDIs). The aim of this study was to perform systematic evaluation of plasma data obtained for 20 endogenous molecules in the same healthy subjects (n = 8-12) in the absence and presence of organic anion transporting polypeptide (OATP) inhibitor rifampicin (600 mg, single dose). The extent of rifampicin DDI magnitude [the ratio of the plasma concentration-time area under the curve (AUCR)], estimated fraction transported (fT), and baseline variability was compared across the biomarkers and relative to rosuvastatin and coproporphyrin I (CPI). Out of the 20 biomarkers investigated tetradecanedioate (TDA), hexadecanedioate (HDA), glycocholic acid, glycodeoxycholic acid (GDCA), taurodeoxycholic acid (TDCA), and coproporphyrin III (CPIII) showed the high AUCR (2.1-8.5) and fT (0.5-0.76) values, indicative of substantial OATP1B-mediated transport. A significant positive correlation was observed between the individual GDCA and TDCA AUCRs and the magnitude of rosuvastatin-rifampicin interaction. The CPI and CPIII AUCRs were significantly correlated, but no clear trend was established with the rosuvastatin AUCR. Moderate interindividual variability (15%-62%) in baseline exposure and AUCR was observed for TDA, HDA, and CPIII. In contrast, bile acids demonstrated high interindividual variability (69%-113%) and significant decreases in baseline plasma concentrations during the first 4 hours. This comprehensive analysis in the same individuals confirms that none of the biomarkers supersede CPI in the evaluation of OATP1B-mediated DDI risk. Monitoring of CPI and GDCA/TDCA may be beneficial for dual OATP1B/sodium-taurocholate cotransporting polypeptide inhibitors with consideration of challenges associated with large inter- and intraindividual variability observed for bile acids. Benefit of monitoring combined biomarkers (CPI, one bile acid and one fatty acid) needs to be confirmed with larger data sets and against multiple OATP1B clinical probes and perpetrators.

Gaining Mechanistic Insight Into Coproporphyrin I as Endogenous Biomarker for OATP1B-Mediated Drug-Drug Interactions Using Population Pharmacokinetic Modeling and Simulation.

This study evaluated coproporphyrin I (CPI) as a selective endogenous biomarker of OATP1B-mediated drug-drug interactions (DDIs) relative to clinical probe rosuvastatin using nonlinear mixed-effect modeling. Plasma and urine CPI data in the presence/absence of rifampicin were modeled to describe CPI synthesis, elimination clearances, and obtain rifampicin in vivo OATP Ki. The biomarker showed stable interoccasion baseline concentrations and low interindividual variability (<25%) in subjects with wildtype SLCO1B1. Biliary excretion was the dominant CPI elimination route (maximal >85%). Estimated rifampicin in vivo unbound OATP Ki (0.13 µM) using CPI data was 2-fold lower relative to rosuvastatin. Model-based simulations and power calculations confirmed sensitivity of CPI to identify moderate and weak OATP1B inhibitors in an adequately powered clinical study. Current analysis provides the most detailed evaluation of CPI as an endogenous OATP1B biomarker to support optimal DDI study design; further pharmacogenomic and DDI data with a panel of inhibitors are required.

Use of mechanistic modeling to assess interindividual variability and interspecies differences in active uptake in human and rat hepatocytes.

Interindividual variability in activity of uptake transporters is evident in vivo, yet limited data exist in vitro, confounding in vitro-in vivo extrapolation. The uptake kinetics of seven organic anion-transporting polypeptide substrates was investigated over a concentration range in plated cryopreserved human hepatocytes. Active uptake clearance (CL(active, u)), bidirectional passive diffusion (P(diff)), intracellular binding, and metabolism were estimated for bosentan, pitavastatin, pravastatin, repaglinide, rosuvastatin, telmisartan, and valsartan in HU4122 donor using a mechanistic two-compartment model in Matlab. Full uptake kinetics of rosuvastatin and repaglinide were also characterized in two additional donors, whereas for the remaining drugs CL(active, u) was estimated at a single concentration. The unbound affinity constant (K(m, u)) and P(diff) values were consistent across donors, whereas V(max) was on average up to 2.8-fold greater in donor HU4122. Consistency in K(m, u) values allowed extrapolation of single concentration uptake activity data and assessment of interindividual variability in CL(active) across donors. The maximal contribution of active transport to total uptake differed among donors, for example, 85 to 96% and 68 to 87% for rosuvastatin and repaglinide, respectively; however, in all cases the active process was the major contributor. In vitro-in vivo extrapolation indicated a general underprediction of hepatic intrinsic clearance, an average empirical scaling factor of 17.1 was estimated on the basis of seven drugs investigated in three hepatocyte donors, and donor-specific differences in empirical factors are discussed. Uptake K(m, u) and CL(active, u) were on average 4.3- and 7.1-fold lower in human hepatocytes compared with our previously published rat data. A strategy for the use of rat uptake data to facilitate the experimental design in human hepatocytes is discussed.

Simultaneous assessment of uptake and metabolism in rat hepatocytes: a comprehensive mechanistic model.

Kinetic parameters describing hepatic uptake in hepatocytes are frequently estimated without appropriate incorporation of bidirectional passive diffusion, intracellular binding, and metabolism. A mechanistic two-compartment model was developed to describe all of the processes occurring during the in vitro uptake experiments performed in freshly isolated rat hepatocytes plated for 2 h. Uptake of rosuvastatin, pravastatin, pitavastatin, valsartan, bosentan, telmisartan, and repaglinide was investigated over a 0.1 to 300 µM concentration range at 37°C for 2 or 45-90 min; nonspecific binding was taken into account. All concentration-time points were analyzed simultaneously by using a mechanistic two-compartment model describing uptake kinetics [unbound affinity constant (K(m,u)), maximum uptake rate (V(max)), unbound active uptake clearance (CL(active,u))], passive diffusion [unbound passive diffusion clearance (P(diff,u))], and intracellular binding [intracellular unbound fraction (fu(cell))]. When required (telmisartan and repaglinide), the model was extended to account for the metabolism [unbound metabolic clearance (CL(met,u))]. The CL(active,u) ranged 8-fold, reflecting a 11-fold range in uptake K(m,u), with telmisartan and valsartan showing the highest affinity for uptake transporters (K(m,u) <10 µM). Both P(diff,u) and fu(cell) span over two orders of magnitude and reflected the lipophilicity of the drugs in the dataset. An extended incubation time allowed steady state to be reached between media and intracellular compartment concentrations and reduced the error in certain parameter estimates observed with shorter incubation times. Active transport accounted for >70% of total uptake for all drugs investigated and was 4- and 112-fold greater than CL(met,u) for telmisartan and repaglinide, respectively. Modeling of uptake kinetics in conjunction with metabolism improved the precision of the uptake parameter estimates for repaglinide and telmisartan. Recommendations are made for uptake experimental design and modeling strategies.

Prediction of human renal clearance from preclinical species for a diverse set of drugs that exhibit both active secretion and net reabsorption.

Identifying any extrahepatic excretion phenomenon in preclinical species is crucial for an accurate prediction of the pharmacokinetics in man. This understanding is particularly key for drugs with a small volume of distribution, because they require an especially low total clearance to be suitable for a once-a-day dosing regimen in man. In this study, three animal scaling techniques were applied for the prediction of the human renal clearance of 36 diverse drugs that show active secretion or net reabsorption: 1) direct correlations between renal clearance in man and each of the two main preclinical species (rat and dog); 2) simple allometry; and 3) Mahmood's renal clearance scaling method. The results show clearly that the predictions to man for the methods are improved significantly when corrections are made for species differences in plasma protein binding. Overall, the most accurate predictions were obtained by using a direct correlation with the dog renal clearance after correcting for differences in plasma protein binding and kidney blood flow (r² = 0.84), where predictions, on average, were within 2-fold of the observed renal clearance values in human.

A rapid computational filter for predicting the rate of human renal clearance.

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.