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While HIV‐1 continues to spread, the use of antivirals in preexposure prophylaxis (PrEP) has recently been suggested. Here we present a modular systems pharmacology modeling pipeline, predicting PrEP efficacy of nucleotide reverse transcriptase inhibitors (NRTIs) at the scale of reverse transcription, target‐cell, and systemic infection and after repeated viral exposures, akin to clinical trials. We use this pipeline to benchmark the prophylactic efficacy of all currently approved NRTIs in wildtype and mutant viruses. By integrating pharmacokinetic models, we find that intracellular tenofovir‐diphosphate builds up too slowly to halt infection when taken “on demand” and that lamivudine may substitute emtricitabine in PrEP combinations. Lastly, we delineate factors confounding clinical PrEP efficacy estimates and provide a method to overcome these. The presented framework is useful to screen and optimize PrEP candidates and strategies and to understand their clinical efficacy by integrating the diverse scales which determine PrEP efficacy.

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It is well known that many realistic mathematical models of biological and chemical systems, such as enzyme cascades and gene regulatory networks, need to include stochasticity. These systems can be described as Markov processes and are modelled using the Chemical Master Equation (CME). The CME is a differential-difference equation (continuous in time and discrete in the state space) for the probability of certain state at a given time. The state space is the population count of species in the system. A successful method for computing the CME is the Finite State Projection Method (FSP). In this paper we will give the mathematical background of the FSP and propose a new addition to the FSP which guaranties our approximation to have optimal order.

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Osteoarthritis (OA) is the most common cause of disability in ageing societies, with no effective therapies available to date. Two preclinical models are widely used to validate novel OA interventions (MCL-MM and DMM). Our aim is to discern disease dynamics in these models to provide a clear timeline in which various pathological changes occur. OA was surgically induced in mice by destabilisation of the medial meniscus. Analysis of OA progression revealed that the intensity and duration of chondrocyte loss and cartilage lesion formation were significantly different in MCL-MM vs DMM. Firstly, apoptosis was seen prior to week two and was narrowly restricted to the weight bearing area. Four weeks post injury the magnitude of apoptosis led to a 40–60% reduction of chondrocytes in the non-calcified zone. Secondly, the progression of cell loss preceded the structural changes of the cartilage spatio-temporally. Lastly, while proteoglycan loss was similar in both models, collagen type II degradation only occurred more prominently in MCL-MM. Dynamics of chondrocyte loss and lesion formation in preclinical models has important implications for validating new therapeutic strategies. Our work could be helpful in assessing the feasibility and expected response of the DMM- and the MCL-MM models to chondrocyte mediated therapies.

Objective: Due to the small size of the murine knee joint, extracting the chondrocyte transcriptome from articular cartilage (AC) is a major technical challenge. In this study, we demonstrate a new and pragmatic approach of combining bulk RNA-sequencing (RNA-seq) and single cell (sc)RNA-seq to address this problem. Design:We propose a new cutting strategy of the murine femur which produces three segments with a predictable mixed cell populations, where one segment contains AC and growth plate (GP) chondrocytes, another contains GP chondrocytes, and the last segment contains only bone and bone marrow. We analysed the bulk RNA-seq of the different segments to find common and distinct genes between the segments. Then, the segment containing AC chondrocytes was digested and analysed via scRNA-seq.Results: Differential expression analysis using bulk RNA-seq identified 350 candidate chondrocyte gene in the AC segment. Gene set enrichment analysis of these genes revealed biological processes related-and non-related to chondrocytes, including, cartilage development (adj. p-value: 3.45E-17) and endochondral bone growth (adj. p-value 1.22E-4), respectively.ScRNA-seq of the AC segment found a cluster of 131 cells containing mainly chondrocytes. This cluster had 759 differentially expressed genes which enriched for extracellular matrix organisation (adj. p-value 7.76E-40) and other joint development processes. The intersection of the gene sets of bulk-and scRNA-seq contained 75 genes, where all but ten genes were previously implicated in cartilage homeostasis or osteoarthritis (OA) progression. Conclusions:Our approach has the potential to detect the scarce disease phenotypes of chondrocytes in murine OA models.

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