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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. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk‐based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick‐start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts. [ABSTRACT FROM AUTHOR]

B The added value of I in silico i models (including quantitative systems pharmacology models) for drug development is now unanimously recognized. However, the I in silico i toolbox is rapidly expanding beyond these traditional/historical modeling technologies and new ones have emerged the last decades, including multiphysics simulations, the so-called systems medicine/pharmacology models (QSP) and clinical trial simulation tools ( I in silico i clinical trials). HTA agencies HTA agencies, as regulators, need clear standards and related up-to-date guidance documents to ensure a correct assessment of the novel drugs developed with the support of I in silico i models. [Extracted from the article]

Background: Complex immunophenotypic repertoires defining discrete adipose-derived stem cell (ASC) subpopulations may hold a key toward identifying predictors of clinical utility. To this end, we sorted out of the freshly established ASCs four subpopulations (SPs) according to a specific pattern of co-expression of six surface markers, the CD34, CD73, CD90, CD105, CD146, and CD271, using polychromatic flow cytometry. Method: Using flow cytometry-associated cell sorting and analysis, gating parameters were set to select for a CD73+CD90 +CD105+ phenotype plus one of the four following combinations, CD34-CD146-CD271- (SP1), CD34-CD146+CD271- (SP2), CD34+CD146+CD271- (SP3), and CD34-CD146+CD271+ (SP4). The SPs were expanded 700- to 1000-fold, and their surface repertoire, trilineage differentiation, and clonogenic potential, and the capacity to support wound healing were assayed. Results: Upon culturing, the co-expression of major epitopes, the CD73, CD90, and CD105 was maintained, while regarding the minor markers, all SPs reverted to resemble the pre-sorted population with CD34-CD146-CD271- and CD34-CD146+CD271- representing the most prevalent combinations, followed by less frequent CD34+CD146-CD271- and CD34+CD146+CD271- variants. There was no difference in the efficiency of adipo-, osteo-, or chondrogenesis by cytochemistry and real-time RT-PCR or the CFU capacity between the individual SPs, however, the SP2CD73+90+105+34-146+271- outperformed others in terms of wound healing. Conclusions: Our study shows that ASCs upon culturing inherently maintain a stable distribution of immunophenotype variants, which may potentially disguise specific functional properties of particular downstream lines. Furthermore, the outlined approach suggests a paradigm whereby discrete subpopulations could be identified to provide for a therapeutically most relevant cell product. [ABSTRACT FROM AUTHOR]