As there are no clear on-target mechanisms that explain the increased risk for thrombosis and viral infection or reactivation associated with JAK inhibitors, the observed elevated risk may be a result of an off-target effect. Computational approaches combined with in vitro studies can be used to predict and validate the potential for an approved drug to interact with additional (often unwanted) targets and identify potential safety-related concerns. Potential off-targets of the JAK inhibitors baricitinib and tofacitinib were identified using two established machine learning approaches based on ligand similarity. The identified targets related to thrombosis or viral infection/reactivation were subsequently validated using in vitro assays. Inhibitory activity was identified for four drug-target pairs (PDE10A [baricitinib], TRPM6 [tofacitinib], PKN2 [baricitinib, tofacitinib]). Previously unknown off-target interactions of the two JAK inhibitors were identified. As the proposed pharmacological effects of these interactions include attenuation of pulmonary vascular remodeling, modulation of HCV response, and hypomagnesemia, the newly identified off-target interactions cannot explain an increased risk of thrombosis or viral infection/reactivation. While further evidence is required to explain both the elevated thrombosis and viral infection/reactivation risk, our results add to the evidence that these JAK inhibitors are promiscuous binders and highlight the potential for repurposing.

Purpose: With increased concomitant chronic diseases in type 2 diabetes mellitus (T2DM), the use of multiple drugs increases as well as the risk of drug-drug interactions (DDI) and adverse drug reactions (ADR). Nevertheless, how medication patterns vary in T2DM patients across different sex and age groups is unclear. This study aims to identify and quantify common drug combinations in first-time metformin users with polypharmacy (≥5 co-medications).

Aims:To estimate the prevalence of potentially inappropriate prescriptions (PIPs) in patients starting their first non-insulin antidiabetic treatment (NIAD) using two explicit process measures of the appropriateness of prescribing in UK primary care, stratified by age and polypharmacy status.Methods:A descriptive cohort study between 2016 and 2019 was conducted to assess PIPs in patients aged ≥45 years at the start of their first NIAD, stratified by age and polypharmacy status. The American Geriatrics Society (AGS) Beers criteria 2015 was used for older (≥65 years) and the Prescribing Optimally in Middle-age People's Treatments (PROMPT) criteria for middle-aged (45-64 years) patients. Prevalence of overall PIPs and individual PIPs criteria was reported using the IQVIA Medical Research Data incorporating THIN, a Cegedim Database of anonymised electronic health records in the UK.Results:Among 28,604 patients initiating NIADs, 18,494 (64.7%) received polypharmacy. In older and middle-aged patients with polypharmacy, 39.6% and 22.7%, respectively, received ≥1 PIPs. At the individual PIPs level, long-term PPI use and strong opioid without laxatives were the most frequent PIPs among older and middle-aged patients with polypharmacy (11.1% and 4.1%, respectively).Conclusions:This study revealed that patients starting NIAD treatment receiving polypharmacy have the potential for pharmacotherapy optimisation.

Background:The JAK inhibitors (JAKi’s) tofacitinib and baricitinib are new alternatives for treating rheumatoid arthritis. Safety concerns associated with JAKi’s, such as the increased risk for thrombosis and viral infections, have emerged worldwide. The underlying explanatory mechanisms remain unknown, suggesting the elevated risk is likely due to underlying confounding or an off-target binding effect. Computational approaches can explore the potential for a small molecule drug to interact with previously unknown biological targets and identify potential safety-related concerns, and open doors for potential drug repurposing.Objectives:To identify and characterize the off-target binding effects of baricitinib and tofacitinib, with a focus on targets related to thrombosis and viral infectionMethods:Potential targets of baricitinib and tofacitinib were predicted using two neural-network-based systems (TIGER[1] and SPiDER[2]). Targets were considered relevant if they had (1) a SPiDER confidence with p<0.05, or (2) a TIGER score >1. Selected targets related to the outcome of interest were experimentally evaluated at Eurofins Cerep (France-Celle L’Evescault, www.eurofins.com) if commercial available. Compounds were tested at (1) single concentration (30 µM) with technical replicates, using radioligand or enzymatic assays, or (2) multiple concentrations (30 µM highest concentration; dilution factor in a log-scale) with technical replicates, using calcium flux or inhibition of [cAMP] assays. Observed activity of ≥50% inhibition or stimulation on the target was considered active, between 25 to 50% inhibition (or a dissociation constant [Kd] from 1 to 10 µM) was considered as moderate activity, and lower than 25% was considered inactive. Dose-response curve were performed on active and moderate targets for IC50 / EC50 (half maximal inhibitory / effective concentration) determination.Results:TIGER and SPiDER suggested a total of 99 off-target binding effects (baricitinib n=41; tofacitinib n=58), of which 17 targets had potential impact on thrombosis or viral infection (baricitinib n=5 and 4, respectively; tofacitinib n=5 and 3, respectively). Commercial testing was available on 11 targets (Adenosine Receptor A2A [AA2AR], Epidermal growth factor receptor, induclible NOS, PI3 Kinase (p110b/p85a), Phosphodiesterase 10A2 [PDE10A2] and Protein Kinase N2 [PKN2] for baricitinib; and Adenosine receptor A3, 15-Lipoxygenase [15-LO], PKN2, Transient receptor potential cation channel [TRPM6] and AA2AR for tofacitinib). Of these, 5 targets showed active or moderately active binding activity (baricitinib n=2; tofacitinib n=3), and were tested for dose-response curves. Test results confirmed ligand-binding activity with IC50 on nanomolar (PKN2), and micromolar ranges (PDE10A2 and TRPM6).Conclusion:The results suggest both baricitinib and tofacitinib are promiscuous binders with effects on several families. Although it may lead to side effects, off-target binding also represents a potential opportunity for drug repurposing. Besides on-target effects, both drugs are under clinical investigation for the treatment of COVID-19 due to off-target interactions. The proposed pharmacological off-target effects of those with active binding include attenuation of pulmonary vascular remodeling, anti-fibrotic and anti-psychotic activities (PDE10A2), modulation of viral response (PKN2), and hypomagnesaemia (TRPM6), which is involved in cardiovascular diseases. This study supports tofacitinib and baricitinib as candidates for drug repurposing (e.g., in COVID-19, Hepatitis C virus, and pulmonary hypertension). We did not identify active off-target interactions linked to thrombosis to explain the elevated risk observed in clinical practice. Further research is required to elucidate the underlying patient-specific factors (confounders) that could explain this safety concern.References:[1]Schneider P et al. Angew Chem Int Ed 2017;56:11520–4.[2]Reker D et al. PNAS 2014;111:4067–72.Disclosure of Interests:None declared

Objectives: There are no clear on-target mechanisms that explain the increased risk for thrombosis and viral infection or reactivation associated with Janus kinase (JAK) inhibitors. We aimed to identify and validate off-target binding effects of the JAK inhibitors baricitinib and tofacitinib using computational and experimental methods. Methods: Potential biological targets of baricitinib and tofacitinib were predicted using two established computational methods. Targets related to thrombosis or viral infection/reactivation were experimentally validated using biochemical and cell-based in vitro assays. Results: Overall, 98 targets were predicted by the computational methods (baricitinib n=41; tofacitinib n=58), of which 17 drug-target pairs were related to thrombosis (n=10) or viral infection/reactivation (n=7), and 11 were commercially available for in vitro analysis. Inhibitory activity was identified in vitro for four drug-target pairs – two related to thrombosis in the micromolar range (phosphodiesterase 10A [baricitinib], transient receptor potential cation channel subfamily M subtype 6 [tofacitinib]) and two related to viral infection/reactivation in the nanomolar range (Serine/threonine protein kinase N2 [baricitinib, tofacitinib]). Conclusions: Previously unknown off-target interactions for the two JAK inhibitors were identified. The proposed pharmacological off-target effects include attenuation of pulmonary vascular remodeling, modulation of Hepatitis C viral response and hypomagnesemia. Off-target effects related to an increased risk of thrombosis or viral infection/reactivation for baricitinib and tofacitinib were not identified. Further clinical and experimental research is required to explain the observed thrombosis and viral infection/reactivation risk.