Prescription Advice Based on Data of Drug-Drug-Gene Interaction of Patients with Polypharmacy.

Purpose: Pharmacogenetic counselling is a complex task and requires the efforts of an interdisciplinary team, which cannot be implemented in most cases. Therefore, simple rules could help to minimize the risk of medications incompatible with each other or with frequent genetic variants. Patients and Methods: One hundred and eighty-four multi-morbid Caucasian patients suffering from side effects or inefficient therapy were enrolled and genotyped. Their medication was analyzed by a team of specialists using Drug-PIN® (medication support system) and individual recommendations for 34 drug classes were generated. Results: In each of the critical drug classes, 50% of the drugs cannot be recommended to be prescribed in typical drug cocktails. PPIs and SSRI/SNRIs represent the most critical drug classes without showing a single favorable drug. Among the well-tolerated drugs (not recommended for less than 5% of the patients) are metamizole, celecoxib, olmesartan and famotidine. For each drug class, a ranking of active ingredients according to their suitability is presented. Conclusion: Genotyping and its profound analysis are not available in many settings today. The consideration of frequent alterations of metabolic elimination routes and drug-drug-gene interactions by using simple rankings can help to avoid many incompatibilities, side effects and inefficient therapies.

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.

ProTox-II: a webserver for the prediction of toxicity of chemicals.

Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity.

CancerResource: a comprehensive database of cancer-relevant proteins and compound interactions supported by experimental knowledge.

During the development of methods for cancer diagnosis and treatment, a vast amount of information is generated. Novel cancer target proteins have been identified and many compounds that activate or inhibit cancer-relevant target genes have been developed. This knowledge is based on an immense number of experimentally validated compound-target interactions in the literature, and excerpts from literature text mining are spread over numerous data sources. Our own analysis shows that the overlap between important existing repositories such as Comparative Toxicogenomics Database (CTD), Therapeutic Target Database (TTD), Pharmacogenomics Knowledge Base (PharmGKB) and DrugBank as well as between our own literature mining for cancer-annotated entries is surprisingly small. In order to provide an easy overview of interaction data, it is essential to integrate this information into a single, comprehensive data repository. Here, we present CancerResource, a database that integrates cancer-relevant relationships of compounds and targets from (i) our own literature mining and (ii) external resources complemented with (iii) essential experimental and supporting information on genes and cellular effects. In order to facilitate an overview of existing and supporting information, a series of novel information connections have been established. CancerResource addresses the spectrum of research on compound-target interactions in natural sciences as well as in individualized medicine; CancerResource is available at: http://bioinformatics.charite.de/cancerresource/.

Volumetric tissue reduction in radiofrequency surgery of the tongue base.

OBJECTIVES: Radiofrequency surgery is a minimally invasive technique for the treatment of the tongue base in sleep-disordered breathing. The aim of this study was to evaluate the changes in upper airway anatomy induced by radiofrequency surgery with MRI. STUDY DESIGN AND SETTING: 10 patients with sleep-disordered breathing were treated with radiofrequency surgery at tongue base. MRI measurements were performed before and after surgery with the help of a recently published protocol. RESULTS: The mean total number of energy delivered per patient was 4750 +/- 1641 Joule. Relevant changes could be observed neither for tongue volume or dimension nor for retrolingual space. CONCLUSIONS: Changes in upper airway anatomy could not be demonstrated. The effects of radiofrequency surgery of the tongue base may more likely be a result of changes in upper airway collapsibility. SIGNIFICANCE: Functional effects of surgical interventions in sleep-disordered breathing should be considered in addition to mechanistic concepts alone.

Lesion formation in radiofrequency surgery of the tongue base.

OBJECTIVES: Temperature controlled radiofrequency volumetric tissue reduction (RFVTR) of the tongue base is a minimally invasive technique for the treatment of obstructive sleep apnea. But despite its widespread use, little is yet known about in vivo effects in humans. Such knowledge would be essential for evidence-based criteria in the selection of energy application. METHODS: In a preparatory in vitro study, porcine tongues were preserved in growing medium. Lesions with different amounts of energy were applied, and maximum diameters were assessed. In the in vivo study, 11 patients were treated with RFVTR at the tongue base by employing different energy levels (800, 600, 400, or 200 J) on two application sites. Magnetic resonance imagery scans were performed 4 to 6, 8 to 10, and 24 hours after surgery. An inversion recovery technique was used to visualize the lesions. RESULTS: RFVTR created lesions at the porcine tongue from 50 J and higher. Maximum lesion sizes were achieved with 400 J. In vivo, all the lesions were clearly visible in the postoperative scans. Lesion size increased with the amount of energy applied. Maximum diameters were created from 600 J and higher. Higher amounts of energy only resulted in a slight increase in lesion length. CONCLUSIONS: The application of 600 J at 85 degrees C leads to optimal lesion sizes. Higher amounts of energy will not lead to a relevant increase in tissue necrosis. With regard to the time needed for application, 600 J appears to be the ideal adjustment for energy delivery in the treatment of the human tongue.