Opportunities and challenges for applying model-informed drug development approaches to gene therapies

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Whole-Body Disposition and Physiologically Based Pharmacokinetic Modeling of Adeno-Associated Viruses and the Transgene Product

To facilitate model-informed drug development (MIDD) of adeno-associated virus (AAV) therapy, here we have developed a physiologically based pharmacokinetic (PBPK) model for AAVs following preclinical investigation in mice. After 2E11 Vg/mouse dose of AAV8 and AAV9 encoding a monoclonal antibody (mAb) gene, whole-body disposition of both the vector and the transgene mAb was evaluated over 3 weeks. At steady-state, the following tissue-to-blood (T/B) concentration ratios were found for AAV8/9: ∼50 for liver; ∼10 for heart and muscle; ∼2 for brain, lung, kidney, adipose, and spleen; ≤1 for bone, skin, and pancreas. T/B values for mAb were compared with the antibody biodistribution coefficients, and five different clusters of organs were identified based on their transgene expression profile. All the biodistribution data were used to develop a novel AAV PBPK model that incorporates: (i) whole-body distribution of the vector; (ii) binding, internalization, and intracellular processing of the vector; (iii) transgene expression and secretion; and (iv) whole-body disposition of the secreted transgene product. The model was able to capture systemic and tissue PK of the vector and the transgene-produced mAb reasonably well. Pathway analysis of the PBPK model suggested that liver, muscle, and heart are the main contributors for the secreted transgene mAb. Unprecedented PK data and the novel PBPK model developed here provide the foundation for quantitative systems pharmacology (QSP) investigations of AAV-mediated gene therapies. The PBPK model can also serve as a quantitative tool for preclinical study design and preclinical-to-clinical translation of AAV-based gene therapies.

Challenges, approaches and enablers: effectively triangulating towards dose selection in pediatric rare diseases

Dose selection is an integral part of a molecule's journey to become medicine. On top of typical challenges faced in dose selection for more common diseases, pediatric rare disease has additional unique challenges due to the combination of 'rare' and 'pediatric' populations. Using the central theme of maximizing 'relevant' information to overcome information paucity, dose selection strategy in pediatric rare diseases is discussed using a triangulation concept involving challenges, approaches and very importantly, enablers. Using actual examples, unique scenarios are discussed where specific enablers allowed certain approaches to be used to overcome the challenges. The continued need for model-informed drug development is also discussed using examples of where modeling and simulation tools have been successfully used in bridging available information to select pediatric doses in rare disease. Additionally, challenges with translation and associated dose selection of new modalities such as gene therapy in rare diseases are examined with the lens of continuous learning and knowledge development that will enable pediatric dose selection of these modalities with confidence.

Model-Informed Approaches and Innovative Clinical Trial Design for Adeno-Associated Viral Vector-Based Gene Therapy Product Development: A White Paper

The promise of viral vector-based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life-threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno-associated virus (AAV) vector-based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype-phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit-risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model-informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV-based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.

Clinical Pharmacology and Translational Considerations in the Development of CRISPR-Based Therapies

Genome editing holds the potential for curative treatments of human disease, however, clinical realization has proven to be a challenging journey with incremental progress made up until recently. Over the last decade, advances in clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) systems have provided the necessary breakthrough for genome editing in the clinic. The progress of investigational CRISPR therapies from bench to bedside reflects the culmination of multiple advances occurring in parallel, several of which intersect with clinical pharmacology and translation. Directing the CRISPR therapy to the intended site of action has necessitated novel delivery platforms, and this has resulted in special considerations for the complete characterization of distribution, metabolism, and excretion, as well as immunogenicity. Once at the site of action, CRISPR therapies aim to make permanent alterations to the genome and achieve therapeutically relevant effects with a single dose. This fundamental aspect of the mechanism of action for CRISPR therapies results in new considerations for clinical translation and dose selection. Early advances in model-informed development of CRISPR therapies have incorporated key facets of the mechanism of action and have captured hallmark features of clinical pharmacokinetics and pharmacodynamics from phase I investigations. Given the recent emergence of CRISPR therapies in clinical development, the landscape continues to evolve rapidly with ample opportunity for continued innovation. Here, we provide a snapshot of selected topics in clinical pharmacology and translation that has supported the advance of systemically administered in vivo and ex vivo CRISPR-based investigational therapies in the clinic.

Best Practices and Considerations for Clinical Pharmacology and Pharmacometric Aspects for Optimal Development of CAR-T and TCR-T Cell Therapies: An Industry Perspective

With the promise of a potentially "single dose curative" paradigm, CAR-T cell therapies have brought a paradigm shift in the treatment and management of hematological malignancies. Both CAR-T and TCR-T cell therapies have also made great progress toward the successful treatment of solid tumor indications. The field is rapidly evolving with recent advancements including the clinical development of "off-the-shelf" allogeneic CAR-T therapies that can overcome the long and difficult "vein-to-vein" wait time seen with autologous CAR-T therapies. There are unique clinical pharmacology, pharmacometric, bioanalytical, and immunogenicity considerations and challenges in the development of these CAR-T and TCR-T cell therapies. Hence, to help accelerate the development of these life-saving therapies for the patients with cancer, experts in this field came together under the umbrella of International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) to form a joint working group between the Clinical Pharmacology Leadership Group (CPLG) and the Translational and ADME Sciences Leadership Group (TALG). In this white paper, we present the IQ consortium perspective on the best practices and considerations for clinical pharmacology and pharmacometric aspects toward the optimal development of CAR-T and TCR-T cell therapies.

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.

Interspecies normalization of dose-response relationship for adeno-associated virus-mediated haemophilia gene therapy-Application to human dose prediction

AIMS

The aim of this study is to develop an approach to predict human dose-response relationship and first-in-human (FIH) dose for adeno-associated virus (AAV)-mediated haemophilia gene therapy.

METHODS

Preclinical dose-response relationships of 7 AAV vectors were normalized to a species-invariant scale using an exponent of 0.25, and the normalized dose-response relationship was then used for FIH dose prediction. The performance of this dose-response normalization approach for FIH dose prediction was compared to that of direct body weight-based dose (vg/kg) conversion and allometric scaling approaches.

RESULTS

A power regression analysis of normalized factor VIII (FVIII) or factor IX (FIX) showed a moderate-to-strong correlation between FVIII or FIX and vector dose across 3 species (R² ranged 0.59 to 0.89), indicating it was feasible to normalize dose-response in multiple species to a species-invariant scale. When the mean values of normalized FVIII or FIX at each dose level were used for regression, the R² values of the 7 vectors were improved to be >0.84. The FIH doses predicted by the 3 approaches were ranked as allometric scaling > dose-response normalization > direct vg/kg conversion for all vectors except for rAAV2-hAAT-FIX and scAAV2/8-LP1-hFIXco. Among the 7 vectors, dose-response normalization, direct vg/kg conversion and allometric scaling generated accurate FIH dose predictions for 2, 2 and 3 vectors, respectively.

CONCLUSION

This study first demonstrated that it is feasible to normalize dose-response relationship of AAV-mediated haemophilia gene therapy in multiple species to a species-invariant scale. The normalized dose-response relationship from preclinical species was successfully extrapolated to patients for FIH dose prediction.

Oncolytic viral kinetics mechanistic modeling of Talimogene Laherparepvec (T-VEC) a first-in-class oncolytic viral therapy in patients with advanced melanoma

Talimogene Laherparepvec (T-VEC) is a first-in-class oncolytic virotherapy approved for the treatment of unresectable melanoma recurrent after initial surgery. Biodistribution data from a phase II study was used to develop a viral kinetic mechanistic model describing the interaction between cytokines such as granulocyte-macrophage colony-stimulating factor (GM-CSF), the immune system, and T-VEC treatment. Our analysis found that (1) the viral infection rate has a great influence on T-VEC treatment efficacy; (2) an increase in T-VEC dose of 10² plaque-forming units/ml 21 days and beyond after the initial dose of T-VEC resulted in an ~12% increase in response; and (3) at the systemic level, the ratio of resting innate immune cells to the death rate of innate immune impact T-VEC treatment efficacy. This analysis clarifies under which condition the immune system either assists in eliminating tumor cells or inhibits T-VEC treatment efficacy, which is critical to both efficiently design future oncolytic agents and understand cancer development.

First-in-Patient Dose Prediction for Adeno-Associated Virus-Mediated Hemophilia Gene Therapy Using Allometric Scaling

In this study, the author compared the performance of two allometric scaling approaches and body-weight-based dose conversion approach for first-in-patient (FIP) dose prediction for adeno-associated virus (AAV)-mediated hemophilia gene therapy using preclinical and clinical efficacy data of nine AAV vectors. In general, body-weight-based direct conversion of effective doses in monkeys or dogs was more likely to underestimate FIP dose but worked for one bioengineered vector with a high transduction efficiency specifically in humans. In contrast, allometric scaling between gene efficiency factor (log GEF) and body weight (log W) was likely to overestimate FIP dose but worked for two vectors with capsid-specific T-cell responses in patients. The third approach, allometric scaling between log GEF and W^-0.25 was appropriate for FIP dose prediction in the absence of T-cell responses to AAV vectors or a dramatic difference in vector transduction efficiency between animals and humans.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Review: Role of Model-Informed Drug Development Approaches in the Lifecycle of Drug Development and Regulatory Decision-Making

Model-informed drug development (MIDD) is a powerful approach to support drug development and regulatory review. There is a rich history of MIDD applications at the U.S. Food and Drug Administration (FDA). MIDD applications span across the life cycle of the development of new drugs, generics, and biologic products. In new drug development, MIDD approaches are often applied to inform clinical trial design including dose selection/optimization, aid in the evaluation of critical regulatory review questions such as evidence of effectiveness, and development of policy. In the biopharmaceutics space, we see a trend for increasing role of computational modeling to inform formulation development and help strategize future in vivo studies or lifecycle plans in the post approval setting. As more information and knowledge becomes available pre-approval, quantitative mathematical models are becoming indispensable in supporting generic drug development and approval including complex generic drug products and are expected to help reduce overall time and cost. While the application of MIDD to inform the development of cell and gene therapy products is at an early stage, the potential for future application of MIDD include understanding and quantitative evaluation of information related to biological activity/pharmacodynamics, cell expansion/persistence, transgene expression, immune response, safety, and efficacy. With exciting innovations on the horizon, broader adoption of MIDD is poised to revolutionize drug development for greater patient and societal benefit.

Methods for Extrapolating Survival Analyses for the Economic Evaluation of Advanced Therapy Medicinal Products

There are two significant challenges for analysts conducting economic evaluations of advanced therapy medicinal products (ATMPs): (i) estimating long-term treatment effects in the absence of mature clinical data, and (ii) capturing potentially complex hazard functions. This review identifies and critiques a variety of methods that can be used to overcome these challenges. The narrative review is informed by a rapid literature review of methods used for the extrapolation of survival analyses in the economic evaluation of ATMPs. There are several methods that are more suitable than traditional parametric survival modelling approaches for capturing complex hazard functions, including, cure-mixture models and restricted cubic spline models. In the absence of mature clinical data, analysts may augment clinical trial data with data from other sources to aid extrapolation, however, the relative merits of employing methods for including data from different sources is not well understood. Given the high and potentially irrecoverable costs of making incorrect decisions concerning the reimbursement or commissioning of ATMPs, it is important that economic evaluations are correctly specified, and that both parameter and structural uncertainty associated with survival extrapolations are considered. Value of information analyses allow for this uncertainty to be expressed explicitly, and in monetary terms.