Real-world evidence for beneficial effects of dipyrone in 4,278 patients with pulmonary hypertension - Analysis of the risk of ventilation, hospitalization, and agranulocytosis.

INTRODUCTION: Dipyrone has been used as an analgesic for a century, but recently was proposed as a novel therapeutic strategy for the prevention and therapy of pulmonary hypertension (PH). The aim of this study was to analyze whether the risk for ventilation procedures and hospitalization was lower among patients with PH who used dipyrone compared to subjects who did not use dipyrone. MATERIALS AND METHODS: Initially, patients with PH were retrieved from the TriNetX database, whereby subjects who used dipyrone were assigned to cohort I, and cohort II was formed by those individuals who did not use dipyrone. Both cohorts were matched for several variables. The outcomes were requirement for ventilation procedures and hospital admission, whereby the time window to record events was 5 years after diagnosis of PH. Subsequently, risk analysis was carried out, and risk ratio (RR) and odds ratio (OR) were calculated. In addition, the risk of agranulocytosis was determined for both cohorts. RESULTS: Out of 741,875 individuals diagnosed with PH 4,282 and 737,593 patients were assigned to the cohorts I and II. After matching, each cohort accounted for 4,278 individuals. Among the cohorts I and II 10 and 187 individuals required ventilation procedures. The according risks of 0.2% vs. 4.4% were significantly different (p < 0.0001; Log-Rank test). RR and OR were 0.053 and 0.051. Within the cohorts I and II 10 and 1,195 subjects required hospital admission. The risks of hospitalization of 0,4% vs. 27.9% differed significantly (p < 0.0001). RR and OR were 0.016 and 0.012. Among the cohorts I and II 47 and 66 individuals were diagnosed with agranulocytosis, whereby no significance was found (p > 0.05). CONCLUSIONS: The risk for ventilation measures and hospitalization among patients with PH was found to be significantly lower when dipyrone was used. Even though the underlying mechanisms remain unknown to date, they are supposedly mediated by an active metabolite of dipyrone. The obtained results appear to be promising for patients suffering from PH. Hence, the present study may encourage further research.

Man vs. machine: comparison of pharmacogenetic expert counselling with a clinical medication support system in a study with 200 genotyped patients.

BACKGROUND: Medication problems such as strong side effects or inefficacy occur frequently. At our university hospital, a consultation group of specialists takes care of patients suffering from medication problems. Nevertheless, the counselling of poly-treated patients is complex, as it requires the consideration of a large network of interactions between drugs and their targets, their metabolizing enzymes, and their transporters, etc. PURPOSE: This study aims to check whether a score-based decision-support system (1) reduces the time and effort and (2) suggests solutions at the same quality level. PATIENTS AND METHODS: A total of 200 multimorbid, poly-treated patients with medication problems were included. All patients were considered twice: manually, as clinically established, and using the Drug-PIN decision-support system. Besides diagnoses, lab data (kidney, liver), phenotype (age, gender, BMI, habits), and genotype (genetic variants with actionable clinical evidence I or IIa) were considered, to eliminate potentially inappropriate medications and to select individually favourable drugs from existing medication classes. The algorithm is connected to automatically updated knowledge resources to provide reproducible up-to-date decision support. RESULTS: The average turnaround time for manual poly-therapy counselling per patient ranges from 3 to 6 working hours, while it can be reduced to ten minutes using Drug-PIN. At the same time, the results of the novel computerized approach coincide with the manual approach at a level of > 90%. The holistic medication score can be used to find favourable drugs within a class of drugs and also to judge the severity of medication problems, to identify critical cases early and automatically. CONCLUSION: With the computerized version of this approach, it became possible to score all combinations of all alternative drugs from each class of drugs administered ("personalized medication landscape ") and to identify critical patients even before problems are reported ("medication alert"). Careful comparison of manual and score-based results shows that the incomplete manual consideration of genetic specialties and pharmacokinetic conflicts is responsible for most of the (minor) deviations between the two approaches. The meaning of the reduction of working time for experts by about 2 orders of magnitude should not be underestimated, as it enables practical application of personalized medicine in clinical routine.

SuperPain--a resource on pain-relieving compounds targeting ion channels.

Pain is more than an unpleasant sensory experience associated with actual or potential tissue damage: it is the most common reason for physician consultation and often dramatically affects quality of life. The management of pain is often difficult and new targets are required for more effective and specific treatment. SuperPain (http://bioinformatics.charite.de/superpain/) is freely available database for pain-stimulating and pain-relieving compounds, which bind or potentially bind to ion channels that are involved in the transmission of pain signals to the central nervous system, such as TRPV1, TRPM8, TRPA1, TREK1, TRESK, hERG, ASIC, P2X and voltage-gated sodium channels. The database consists of ∼8700 ligands, which are characterized by experimentally measured binding affinities. Additionally, 100 000 putative ligands are included. Moreover, the database provides 3D structures of receptors and predicted ligand-binding poses. These binding poses and a structural classification scheme provide hints for the design of new analgesic compounds. A user-friendly graphical interface allows similarity searching, visualization of ligands docked into the receptor, etc.

SynSysNet: integration of experimental data on synaptic protein-protein interactions with drug-target relations.

We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of ∼1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein-protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein-protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given.