Pharmacology service

Medicilon is recognized one of the leaders of CRO Company in china. With the experienced service and global capabilities in pharmacology study, medicilon offers over 10 years of experience in performing a wide range of pharmacology test services to clients in the pharmaceutical using thoroughly validated animal models to help ensure the accuracy of your results.
Medicilon is able to offer specific pharmacology protocols in multiple therapeutic areas to help identify promising lead compounds. We also welcome the opportunity to develop custom protocols that satisfy your project needs.
• Medicilon has over 100 well-characterized Tumor Cell Line Xenograft models ;
• We offer non-human primates, dogs, mice and rats, rabbits, guinea pigs and others in our services.
Our staff at Medicilon is amongst the most knowledgeable in the industry. Over 50% of our employees have M.S. and Ph. D. degrees, over 10% of them have foreign education and/or working experiences.
Chunlin Chen, Ph.D. CEO, Formally a Staff Investigator for Vertex Pharmaceuticals, Dr. Chen co-founded Medicilon in 2004. Dr Chen is a highly published thought leader in the pharmaceutical industry with extensive experience in academia, pharmaceutical, and regulatory evaluation. Dr. Chen received his PhD from Oklahoma State University and completed postdoctoral training in the United States. He is a Postdoctoral Fellow at the St. Jude Children’s Research Hospital and has held numerous leadership positions in professional scientific trade organizations in China as well as other parts of the world. Dr. Chen has been awarded as special expert under national "Thousand Plan" program.
Dr. Gu was Director of the Toxicology Research Department at the Shanghai Institute of Pharmaceutical Industry – China and Executive Director of the National Shanghai Center for New Drug Safety Evaluation and Research – China. He is the GLP expert of the China State Food and Drug Administration. Dr. Gu was a visiting scholar in the German Houchst Pharmaceutical Company where he did drug preclinical research for two years. He also did short-term visits to GLP laboratories in United States, Canada and Australia. Dr. Gu was the project leader of 973 national projects and a total of 7 projects granted by National Youth New Drug Fund and the Science and Technology Commission of Shanghai Municipality-China. Dr. Gu also received the second prize for Science and Technology Advancement awarded by the Shanghai Municipality-China. He is the member of CFDA, GLP expert group and Chinese Society of Toxicology.
All members of the team are available to advise clients and design and conduct the in vivo/in vitro pharmacology studies. Call medicilon today to speak with one of our experts about your research needs.

Developing and Evaluating Primary Care Anticoagulation Services

All content on this webpage originated from other webpages,Please check the medicilon's website for details. Medicilon offers fully integrated pharmaceutical services for the global scientific community. We focus on providing an exceptional client-centered experience and advancing the drug discovery process.
Email: Marketing@medicilon.com.cn Website: www.medicilon.com
aWarfarin is a drug with proven effectiveness in the prevention of stroke. Patients on warfarin need their therapy to be monitored by regular drug safety evaluation to prevent the occurrence of thrombotic and haemorrhagic events. Traditionally, this anticogulation service has been provided in secondary care anticoagulation clinics. The National Service Framework NSF) for Older People Department of Health 2001a) prioritised reduction in the incidence of stroke, this coupled with the UKs ageing population, has resulted in an expected 10% yearly increase in the demand for anticoagulation services. Current evidence suggests that not all patients who would benefit from warfarin are receiving it and, despite this unmet need, the pressure on the traditional hospital-based sen/ice is already becoming unsustainable. In this study, anticoagulation services at Barts and The London NHS Trust were to be developed and evaluated from a research perspective. Developmental work involved collection and analysis of patient satisfaction data, literature review and multidisciplinary discussions. Evidence from the developmental phase was triangulated and used to develop an intervention study to test the impact of providing anticoagulation services in patients homes.
The intervention was tested in a randomised crossover study comparing two models of domiciliary anticoagulation service for mobility-impaired patients with each other and against the traditional service provision. The first model involved a general phlebotomist obtaining venous samples in the patients homes. All other aspects of the service were provided by the hospital. In the second model, one-stop testing and dosing in the patients homes was performed by a trained pharmacist using near patient drug safety evaluation and software-assisted warfarin dosing. The domiciliary models were evaluated in terms of patient satisfaction, anticoagulation control and safety. aThe findings included equivalent anticoagulation control achieved by the domiciliary/ services compared to that achieved by the traditional hospital-based service. The number of adverse events in the domiciliary services was comparable to that observed in the traditional service. Finally, there was a significant improvement in patient satisfaction with the domiciliary services compared to the traditional service. The results suggest that the evidence based domiciliary anticoagulation service models were suitable alternatives to the traditional anticoagulation service model.

Drug Safety Signal Detection from Online Health Communities

All content on this webpage originated from other webpages,Please check the medicilon's website for details. Medicilon offers fully integrated pharmaceutical services for the global scientific community. We focus on providing an exceptional client-centered experience and advancing the drug discovery process.
Email: Marketing@medicilon.com.cn Website: www.medicilon.com
The development of Web 2.0 and Health 2.0 technologies leads the booming of online health communities (OHCs) such as MedHelp, WebMD and so on. Such platforms are not only empowering individuals to play a substantial role in their own health, but also generating informative consumer-contributed-contents that can be utilized to mine timely and useful knowledge, thus providing automated insights and discovery. Since pharmacovigilance, namely adverse drug reactions (ADRs) and drug-drug interactions (DDIs), represents a serious health problem all over the world, how to detect drug safety evaluation has drawn many researchers’ attention and efforts. Currently, methods proposed to detect ADR and DDI signals are mainly based on traditional data sources such as spontaneous reporting data, electronic health records, pharmaceutical databases, and biomedical literature. However, these data sources are either limited by under-reporting ratio, privacy issues, high cost, or long publication cycle. In this dissertation, we propose to harness consumer-contributedcontents extracted from online health communities for drug safety signal detection and developed various techniques to serve our purpose. Specifically, for ADR detection, we propose to utilize association rule mining to extract associations between drugs and ADRs, and use such measures as confidence, leverage, lift, etc. to capture the association strength. Experiment results demonstrate that our methods are capable of detecting Food and Drug Administration (FDA) alerted ADR signals. Furthermore, we also develop matrix-based and tensor-based techniques to detect ADR signals in a timely manner. The experiment results showed that both approaches are able to detect ADR signals much earlier than FDA’s official alert or labeling revision time. Especially, tensor-based method outperforms matrix-based techniques because they are capable of handling missing data that is quite common in the area of social media, and can better capture and exploit temporal patterns. For DDI detection, we also use association rule mining and propose another measure, namely Interaction Ratio, to capture association strength between two drugs and an ADR. Experiment results demonstrated that our method is able to effectively detect DDIs reported by DrugBank. Other than directly mining consumer-contributed-contents, we also propose to construct a heterogeneous healthcare network based on those contents and to utilize link mining techniques for drug safety signal detection. Concretely, for both ADR and DDI detection problems, we extract topological features from the network, quantify the features using different weighting schemas, and use supervised learning techniques to predict drug safety evaluation. Further, for DDI detection, we propose to detection drug-drug interactions and association ADRs at the same time with triad prediction. Experiment results show that our techniques are effective in discovering both ADR and DDI signals.