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Pharmaceutical Business Intelligence- Going Beyond Numbers. By Prakash SM. The Pharma Reality . Like every other industry… Large amount of data at every stage of the products/ company lifecycle Till 21 CRF R11, a typical US FDA NDA filing was about 21 container trucks large
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Pharmaceutical Business Intelligence- Going Beyond Numbers By Prakash SM
The Pharma Reality Like every other industry… • Large amount of data at every stage of the products/ company lifecycle • Till 21 CRF R11, a typical US FDA NDA filing was about 21 container trucks large • All decision and movement from one stage to the next is essentially data driven • Data accuracy and verifiability critical. But different • Errors have huge costs- • Viaox • Data can be presented in multiple format- qualitative (end points, inclusion criteria etc.) and quantitative (LCMS, QSARs, dose dependency, sales etc) • While the basic intelligence process is the same, the degree of industry information required is deep and varies with each stage of the lifecycle ( highly specialized industry with a vastly varied end-user group)
BI Requirements Change with the Lifecycle Discovery Preclinical Clinical Registration Manufacture Commercial
Clinical Trial Information Data MiningExample of Indegene’s implementation of BI tools and domain skills Background • Clinical trials- Study on human subjects to determine the safety and efficacy of the drug/procedure • No of subjects can vary from 8 to >15000, duration from few weeks to many years • Very closely monitored for • Safety and Efficacy • Competitive monitoring • Predicting the success of the drug- both approval and marketing • Determining the future trends in treatment • Reporting in mandatory in most countries, with specified schedules • Significant amount of data available to public consumption
Clinical Trial Information Data Mining The Challenge • No common repository- over 275 trial sites • Large number of clinical trials – Big sites have over 100000 clinical trials each, average of 2000+ trials • Multiple formats of reporting • Multiple reporting of same trial data • Text and quantitative information mixed, both critical for evaluation • Some degree of search and categorization possible • Needs a lot of reading from multiple sources and further classification to determine any trend • Needs significant understanding of the disease area and expertise- Usually by mid level resources • What is right for one disease need not be right for another
Clinical Trial Information Data Mining The Solution • Comprehensive cloud-based platform for searching and analyzing clinical trials in a given indication/disease area • Clean redundancy from multiple sources, develop standardized parameters • Standardized parameters for each disease area • Allow analysis by parameters specific to each indication Analytical platform of global clinical trials, aimed at aiding clients in their effort to understand specific clinical trial landscapes and their competitive environment. Aimed at a wide variety of functions such as clinical operations, brand management, CI professionals as well as strategic marketing.
Clinical Trial Information Data Mining • Sources: • Clinicaltrials.gov • ANZCTR • ICTRP • ISRCTN • UMIN • Manual • CTRI • UKCRN • NTR • IRCT • JapicCTI • ChiCTR • SANCTR • Publications • Conference presentation Data warehouse Process Human intelligence Trial Analytics Platform Parsers Internal output engine Output Manual tagging of parameters
Indegene soluion:Eg: Breast cancer: Endpoints Distribution Analytics*(1/2) Completed trials have mainly focused on Overall Response Rate and Progression Free Survival as endpoints * For selected drugs
Breast cancer: Endpoints Distribution Analytics*(2/2) Ongoing trials are focused on Overall Response Rate, Progression Free Survival and Disease Free Survival as endpoints * For selected drugs
Breast cancer: Patient Segment Distribution Analytics*(1/2) Molecules of interest were evaluated in first line metastatic breast cancer and in treatment refractory breast cancer * For selected drugs
Breast cancer: Patient Segment Distribution Analytics*(2/2) Majority of molecules are being evaluated in patients with metastatic breast cancer and in primary breast cancer. * For selected drugs
Breast cancer: Site distribution Majority of the clinical trial site are present in North America and Europe. * For selected drugs
Custom Performance BI and ReportingInitial client state Data Sources IMS Midas, NPA, NDTI, NDC AMR, Synovate, Cegedim CAM, CD Promo Impact Rx Company Financial data Data types Sales $ and units Patient level Promotional Financials Analysis • $ share • Unit share • NRx share • TRx share • Sales by indication • Patient share by indication • Continuing patient share • New, switch patient share • Reach & frequency by reps • Samples • Journal ad • Net Sales Reporting by product or franchise (e.g. Oncology, Immunology) Global dashboards for Senior Management Regional dashboards for Regional Teams Country level dashboards for country managers
Solution Options • Indegene provides multiple solutions: • An XML feed delivered from data warehouse servers and read by Excel front end • Custom built analysis and web delivery platform • Business Objects or Cognos based BI platform working along with client’s internal solution
Analysis and delivery platform Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Data source OLTP End users Analysis and Reporting Subscribed data sources Reports Data Warehouse AnalysisServices Country/ Regional reports Operational Data Store(ODS) ReportingServices DataTransformation(DTS) / Extract Transform Load (ETL) Dashboard reports Legacy Extract Clean Conform Deliver Delivery platform- SharePoint, Web Portal, Direct delivery • Delivery Platform include sophisticated Oracle and Cognos toolset for global data connectivity and faster processing of large amount of data from country ops, global etc. Benefit to Client: Reduced cycle time for ongoing reporting Reduced total cost of ownership Standardization, ease of use, compliance
Report Delivery Options/Formats • Delivery Options • Push Method: This type delivery option is preferred for reports with long running times with complex calculations, extensive run-time roll-ups, aggregations etc. All the reports mentioned below can be generated by this approach: • Standardized brand reports • Weekly Performance Reports • Monthly Performance Reports • Quarterly Reports • Pull Method: Suitable for ad-hoc reports that aren’t standardized. • Publishing capabilities • Delivery Formats • MS XLS • MS PPT • PDF • HTML • XML formats • Flash • Web portals • Email reports • Intranet postings • SharePoint
Progressing of the engagement Dashboard Continuum Year 3 Recommendations Year 2 Analysis Year 1 Simple Dashboards • Analysis • Brand X grew its share in this period by y%, which is -% more than the market growth • Recommendations • Sales calls to segment Y physicians need to go up to realize higher share of Brand X • Analysis • Brand X grew its share in this period by y%, which is -% more than the market growth Value
Samples SFE Dashboard Tool to collate and track KPIs across multiple countries Std Performance Dashboard Standardized performance report collation and reporting Therapy Area Dashboard Competitor tracking reporting by TA IMS query service Quick search and reporting for IMS queries Market Performance Tracking IMS driven sales tracking across competitor and regions Product Reports and Market Analysis