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.

Clinical Pharmacology in Drug Development for Rare Diseases in Neurology: Contributions and Opportunities.

Several challenges are associated with rare disease drug development in neurology. In this article, we summarize the US Food and Drug Administration's experience with clinical drug development for rare neurological diseases and discuss clinical pharmacology's critical contributions to drug development for rare diseases. We used publicly available information to identify and screen drug products approved for rare neurological indications between 1983 and 2019. We highlighted cases in which clinical pharmacology contributed to the evidence of drug efficacy, dose selection for pivotal clinical trials, dose optimization based on intrinsic and extrinsic factors, pharmacokinetic bridging for formulations, and efficacy bridging across different racial groups. Fifty-one approved drug products were identified since the introduction of the Orphan Drug Act in 1983. Interestingly, the number of approvals in the last few years increased significantly, probably due to advances in genomic research and targeted drug modalities. Evaluation of dose selection in patient populations showed that in 52% of cases, the sponsors did not evaluate efficacy for more than one or two dose levels throughout the development program. Clinical pharmacology studies to evaluate the effect of intrinsic or extrinsic factors were adequately characterized in most of the applications. With the expansion of model informed drug development applications, (e.g., quantitative systems pharmacology and deep learning neural network models), the role and impact of clinical pharmacology is expected to grow exponentially in the next decade and enhance the development of novel treatment modalities for neurological rare diseases.

Brain-derived neurotrophic factor serum levels and genotype: association with depression during interferon-α treatment.

Depression has been associated with inflammation, and inflammation may both influence and interact with growth factors such as brain-derived neurotrophic factor (BDNF). Both the functional Val66Met BDNF polymorphism (rs6265) and BDNF levels have been associated with depression. It is thus plausible that decreased BDNF could mediate and/or moderate cytokine-induced depression. We therefore prospectively employed the Beck Depression Inventory-II (BDI-II), the Hospital Anxiety and Depression Scale (HADS), and the Montgomery-Asberg Depression Rating Scale (MADRS) in 124 initially euthymic patients during treatment with interferon-alpha (IFN-α), assessing serum BDNF and rs6265. Using mixed-effect repeated measures, lower pretreatment BDNF was associated with higher depression symptoms during IFN-α treatment (F144,17.2=6.8; P<0.0001). However, although the Met allele was associated with lower BDNF levels (F1,83.0=5.0; P=0.03), it was only associated with increased MADRS scores (F4,8.9=20.3; P<0.001), and not the BDI-II or HADS. An exploratory comparison of individual BDI-II items indicated that the Met allele was associated with suicidal ideation, sadness, and worthlessness, but not neurovegetative symptoms. Conversely, the serotonin transporter promoter polymorphism (5-HTTLPR) short allele was associated with neurovegetative symptoms such as insomnia, poor appetite and fatigue, but not sadness, worthlessness, or suicidal ideation. IFN-α therapy further lowered BDNF serum levels (F4,37.7=5.0; P=0.003), but this decrease occurred regardless of depression development. The findings thus do not support the hypothesis that decreasing BDNF is the primary pathway by which IFN-α worsens depression. Nonetheless, the results support the hypothesis that BDNF levels influence resiliency against developing inflammatory cytokine-associated depression, and specifically to a subset of symptoms distinct from those influenced by 5-HTTLPR.