New Horizons of Model Informed Drug Development in Rare Diseases Drug Development.

Model-informed approaches provide a quantitative framework to integrate all available nonclinical and clinical data, thus furnishing a totality of evidence approach to drug development and regulatory evaluation. Maximizing the use of all available data and information about the drug enables a more robust characterization of the risk-benefit profile and reduces uncertainty in both technical and regulatory success. This offers the potential to transform rare diseases drug development, where conducting large well-controlled clinical trials is impractical and/or unethical due to a small patient population, a significant portion of which could be children. Additionally, the totality of evidence generated by model-informed approaches can provide confirmatory evidence for regulatory approval without the need for additional clinical data. In the article, applications of novel quantitative approaches such as quantitative systems pharmacology, disease progression modeling, artificial intelligence, machine learning, modeling of real-world data using model-based meta-analysis and strategies such as external control and patient-reported outcomes as well as clinical trial simulations to optimize trials and sample collection are discussed. Specific case studies of these modeling approaches in rare diseases are provided to showcase applications in drug development and regulatory review. Finally, perspectives are shared on the future state of these modeling approaches in rare diseases drug development along with challenges and opportunities for incorporating such tools in the rational development of drug products.

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.

Antiviral treatment for treatment-naïve chronic hepatitis B: systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Chronic hepatitis B (CHB) infection poses a significant burden to public health worldwide. Most cases are clinically silent until late in the disease course. The main goal of current therapy is to improve survival and quality of life by preventing disease progression to cirrhosis and liver failure, and consequently hepatocellular carcinoma development. The objective of this review is to provide a contemporary and comprehensive evaluation of the effectiveness of treatment options. METHODS: We performed a systematic review of peer-reviewed literature for randomized controlled trials involving treatment-naïve CHB adult population who received antiviral therapy. The endpoints were virologic response (VR), normalization of alanine aminotransferase (ALT norm), HBeAg loss, HBeAg seroconversion, and HBsAg loss for the HBeAg-positive population; and VR and ALT norm for the HBeAg-negative population. Network meta-analysis (NMA) was performed to synthesize evidence on the efficacy of treatment. RESULTS: Forty-two publications were selected. Twenty-three evaluated HBeAg-positive population, 13 evaluated HBeAg-negative population, and six evaluated both. We applied NMA to the efficacy outcomes of the two populations separately. Treatment strategies were ranked by the probability of achieving outcomes, and pairwise comparisons calculated from NMA were reported in odds ratios (OR). For HBeAg-positive population, tenofovir disoproxil fumarate (TDF) and tenofovir alafenamide (TAF) were the best for VR; OR vs adefovir = 14.29, 95% CI 7.69-25 and 12.5, 95% CI 4.35-33.33 respectively. TAF was the best for achieving ALT norm (OR vs placebo = 12.5, 95% CI 4.55-33.33), HBeAg loss, and seroconversion (OR vs entecavir/TDF combination = 3.03, 95% CI 1.04-8.84 and 3.33, 95% CI 1.16-10 respectively). In the HBeAg-negative population, TDF and TAF were the best for VR (OR vs adefovir = 9.79, 95% CI 2.38-42.7 and 11.71, 95% CI 1.03-150.48 respectively). Telbivudine and TAF were the best for ALT norm. Certain nucleos(t)ide combinations also had high probability of achieving positive outcomes. CONCLUSIONS: Our results are consonant with current clinical guidelines and other evidence reviews. For both HBeAg-positive and HBeAg-negative populations, TDF and TAF are the most effective agents for virologic suppression, and TAF is effective across all outcomes.