Virtual patients, digital twins and causal disease models: Paving the ground for in silico clinical trials.

Computational models are being explored to simulate in silico the efficacy and safety of drug candidates and medical devices. Disease models that are based on patients' profiling data are being produced to represent interactomes of genes or proteins and to infer causality in the pathophysiology, which makes it possible to mimic the impact of drugs on relevant targets. Virtual patients designed from medical records as well as digital twins are generated to simulate specific organs and to predict treatment efficacy at the individual patient level.

Innovative medicine development.

Background: In recent years the global landscape of pharmaceutical development has evolved drastically in order to adapt to innovative products such as immunotherapy, regenerative medicines and cell and gene therapy, all offering the hope to cure numerous untreated diseases. The global COVID-19 pandemic also led competent authorities in charge of approval of new medicines to implement adapted regulatory pathways allowing early access to innovative treatments and vaccines. New challenges are to be overcome, it is the short development time, or the small patient populations, or again drug product features requiring complete new production, testing and distribution strategies.

Possible Contexts of Use for In Silico Trials Methodologies: A Consensus-Based Review.

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process.

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility.

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation.

Maternal effects as drivers of sibling competition in a parent-offspring conflict context? An experimental test.

Maternal effects occur when the mother's phenotype influences her offspring's phenotype. In birds, differential allocation in egg yolk components can allow mothers to compensate for the competitive disadvantage of junior chicks. We hypothesize that the parent-older chick conflict peaks at intermediate conditions: parents benefit from the younger chick(s) survival, but its death benefits the older chick in terms of growth and survival.

Accelerating development, registration and access to medicines for rare diseases in the European Union through adaptive approaches: features and perspectives.

There is growing recognition that the current research-and-development (R&D) and innovation-regulation ecosystem could be made more efficient to stimulate and support access to innovative therapies for those patients with rare, life-threatening diseases for which there are no adequate licensed therapies. New and progressive thinking on the principles and processes of drug development and regulation are needed in rare disease settings in order to ensure developments are financially sustainable. This paper presents perspectives on the current and emerging schemes for accelerating development of and access to medicines for rare diseases in the European Union.