Pharmaceutical Technologist - May 2008 - (Page 16)

Integrated safety as clinical scientists, statisticians and pharmacoepidemiologists. Each of these users would need access to different slices of the data and would have access through an intuitive, easy-to-use interface. The platform would offer the following: ● The ability to identify signals using statistical methods or nonstatistical methods across multiple data sources, including bayesian methods, PRR, OR, reporting rate, syndrome, trial drug — comparator. ● A collaborative and secure platform to share and delegate the signals. ● Techniques to reduce the false positive signals. ● The facility to record analysis of the signals. ● The infrastructure can be built on currently available technologies. The data repository can be built using any relational database or SAS 9.1.3. ● An intuitive user interface will need a Microsoft ASP.Net or a J2EE-based implementation. The best approach for combining the integrated safety data with predefined signal detection criteria to enable the signal detection is shown in Figure 2. The platform is envisioned to allow: ● Integrating clinical safety records (E2B) and clinical trial data (CDISC). ● Safety signal detection and signal management system. ● Integrate EHR (HL7) with CDISC. Benefits Such data integration increases patient safety in multiple ways; from increasing the quality of signal detection to enabling faster capture of adverse event data. Advances in clinical research and drug safety surveillance are possible through shared patient health information and an integrated drug safety infrastructure. Using this architecture, healthcare professionals could easily report adverse events using the patient data available in EMRs. It would significantly reduce the time required for processing and assessment of a single case by minimizing the need for follow-ups and ensuring a “right first time” policy. Another business benefit of the integration of preclinical, clinical and postmarketing data, as well as patient health records is that it would enable pharmacoepidemiologists to test hypothesis and evaluate patterns of drug effects across a wide range of patients. Such a repository could even be shared with regulatory bodies; for example, integrating sales data into the safety infrastructure would allow the estimation of patient exposure and allow signal detection using patient exposure parameters. Additionally, integrating genotypic and phenotypic data into the infrastructure could make clinical research more effective. This data could be used to identify and validate biomarkers, which are gaining increasing importance in clinical research. It could also assist in patient stratification and better selection of patients for clinical trials, helping to reduce cycle time and associated costs. It is, therefore, possible to foresee a scenario where integrated data paves the way for targeted medicine — patients can be prescribed medication with a higher probability of success based on their EMRs and genetic data. The road ahead The biggest challenge to this future is not from technology constraints, but in defining policies to prevent misuse of patient data and to define consistent standards to allow interoperability. This hurdle can be broken down into the following considerations: ● One of the key challenges has been the quality and quantity of data available for signal detection, as a safety signal is only as good as the underlying data. Physicians and other healthcare professionals need to be incentivized to increase the ADR reporting and to report them with high-quality supporting patient health information. ● The ownership of patient data and its governance is a key question that remains to be addressed. Would the ownership reside with pharmaceutical companies, insurance companies, hospitals or other independent organizations? There must be strict controls regarding who can aggregate this Figure 2 Combination of integrated safety data with predefined signal detection criteria to enable signal detection. Signal detection module Signal criteria Datamart Extract criteria definition Process Generate signal Notify users Save signal information in datamart AE data Datamart 16 MAY 2008 PHARMACEUTICAL TECHNOLOGIST

Table of Contents Feed for the Digital Edition of Pharmaceutical Technologist - May 2008

Pharmaceutical Technologist - May 2008 Contents Industry Highlights Morpheus Market Watch Pharma’s Need for Integrated Safety Is Pharma’s Future Mobile? Facing the CRO Behemoths Q&A

Pharmaceutical Technologist - May 2008

For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.