Driving Change in Clinical Data Management: A Vision for the Future

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1 White Paper Drivig Chage i Cliical Data Maagemet: A Visio for the Future Rapidly evolvig techology is addressig the pharmaceutical idustry s eed to maage cost pressures ad shorte the time for drug approval. Strategies to make processes leaer are beig revisited, brigig i approaches such as risk-based moitorig ad the use of Electroic Health Records (EHRs). Data-orieted chages have icluded: - Capturig data i real-time - Graphic ad customized slice ad-dice views of data at differet poits i time to assess patiet safety durig the trial - Seamless coversio of data ito meaigful iformatio usig sematic iteroperability supported by data stadardizatio ad employig appropriate data goverace models. While Electroic Data Capture (EDC) ad outsourcig were harbigers of chage i the cliical data maagemet idustry, the cliical data maager eeds to rapidly adapt to better techology ad leaer ad faster processes.

2 About the Author Dr. Nimita Limaye Dr. Nimita Limaye heads the Biometrics ad Medical Writig fuctio at Tata Cosultacy Services Pvt. Lt., Idia ad plays a key role i cotributig to the strategic visio of the life scieces busiess. She has 17 years of experiece workig across both the pharmaceutical ad the CRO sector across diverse fuctioal areas, ad has bee resposible for leadig strategic parterships, across CDM, medical writig ad BSP. She is the Past Chair of Society of Cliical Data Maagemet (SCDM), head-quartered i the US. She also chairs the DIA Idia Medical Writig Workig Group, represets Idia o the SIAC Leadership Coucil ad is the Program Co-Chair for the DIA Idia Aual Coferece. I additio, she is the member of the Natioal Committee o Drugs ad Pharmaceuticals ( ) of the Cofederatio of Idia Idustries. She has spoke at various iteratioal forums ad has several publicatios to her credit. 2

3 Table of Cotets 1. The Drivers of Chage 4 2. Stadardizatio, Itegratio ad Iteroperability 4 3. Cetralized Risk-Based Moitorig ad DDE 5 4. EDC Evolvig Perspectives 6 5. The Future Visio It s About Trasformatio 6 6. Coclusio 7 3

4 The Drivers of Chage Cliical data maagemet as a professio is i a very dyamic state, with multiple factors drivig this chage: New guidaces released by the FDA, such as the Risk-Based Moitorig Guidace ad esource Guidace Rapid strides i techology ad medicie. For example, data is trasmitted wirelessly whe a tablet is cosumed, via Igestible Evet Markers (IEMs), to the ivestigator s database EDC, EMRs, ad multiple Commercial Off The Shelf (COTS) applicatios are available i the market The idustry is icreasigly udergoig mergers ad acquisitios, resultig i large quatities of data with differet structure ad stadards, residig i multiple databases ad ofte i differet applicatios The eed to drive seamless iteroperability across applicatios withi the cliical trial life cycle, so as to miimize the duplicatio of effort ad follow the critical path as drive by the Cliical Trial Trasformatio Iitiative, is a fudametal eed today. The cost of takig a drug from discovery to commercializatio is close to $1.38 billio, as per Tufts R&D Outlook for This has reportedly icreased 7.4% aually over the past 20 years, owig to diverse reasos, ragig from icreasig protocol complexity, larger, global multi-cetric trials, the icreasig cost of techology ad striget compliace criteria to esure patiet safety, to ame a few. Thus, compaies are facig huge cost pressures, resultig i icreased outsourcig, complemeted by the eed to follow a lea approach ad deliver high quality data that esures approval ad patiet safety, albeit at the lowest cost. Evolvig busiess models are apparet - where earlier large pharmaceutical compaies chose to work with multiple vedors, vedor cosolidatio seems to be the curret tred. Also, o-liear growth drivers, such as cost-effective, vedor-maaged, hassle-free e-cliical solutios, which drive the itegratio of data from multiple legacy applicatios ad help sposors partly buffer the impact of suk costs, seem to have become itegral to the busiess solutio Stadardizatio, Itegratio ad Iteroperability The idustry is strivig to reverse the existig Data Rich, Iformatio Poor sceario, focusig o gatherig requisite, reliable ad accurate data ad buildig i supportig aalytics allowig for the meaigful ad timely iterpretatio of the same. As data traverses through multiple chaels such as (Cliical Data Maagemet Systems) CDMS, (Cliical Trial Maagemet Systems) CTMS, (Cliical Data Repositories) CDR, ad SAS Aalytics tools, repeated etry at multiple stages ot oly ivolves extra effort ad delays i timelies, but it also icreases the possibility of errors. I additio, with over 700 mergers havig occurred i the secod half of the last decade, cosolidatio has become the orm. Related challeges like disparate techology platforms, differig data stadards ad varied busiess processes actually defeat the core objective of cosolidatio, amely to brig a drug to the market faster. Various iitiatives are helpig compaies work towards more cost-efficiet ad faster approvals: 4

5 Cliical Data Iterchage Stadards Cosortium (CDISC s) Shared Health ad Cliical Research Electroic library (SHARE), which helps provide stadardized metadata defiitios which ehace commuicatio across trials ad applicatios i studies worldwide Biomedical Research Itegrated Domai Group (BRIDG), which allows pharmaceutical compaies to make more iformed decisios by leveragig iformatio used i cliical trials Cliical Data Acquisitio Stadards Harmoizatio (CDASH), which defies data collectio fields that alig with those required for data submissios for regulatory approval As busiess models chage from trasactioal to strategic, vedors also work towards providig costeffective ad iovative itegratio solutios ad thus also providig a value-add to the partership. Cloudbased solutios are beig desiged to provide both scalable ad flexible architecture, which would allow compaies to: Patch o additioal applicatios (vedor or sposor-specific) Ivolve reusable CDISC compliat data structures Drive process automatio allowig data to be pulled seamlessly from multiple sources ito a stadardized format ad stored i a cliical data repository Create real-time tredig reports across patiets ad studies through user-friedly graphic user iterfaces (GUIs) Support meta-aalyses These address a importat gap, as the itegratio of multiple sources of data to provide tredig reports that provide a holistic overview of the coditio of the patiet or the study is ofte missig; i additio, close to 100% of compaies that are usig e-cliical techologies are still usig exteral software to support aalytics. Blue-tooth eabled data trasmissio, viewig reports real-time o oe s mobile or IPAD are ot a futuristic visio, but also a happeig reality. Cetralized Risk-Based Moitorig ad DDE It is e mperative that techology-eabled busiess models supportig Targeted Source Data Verificatio (SDV) ad Risk Based Moitorig are established, wherei viewig data real time ad leveragig real-time tredig reports across patiets would cotribute sigificatly to risk assessmet ad ehaced patiet safety. While 30% of the cost of a trial is cotributed by moitorig, 46% of the moitorig effort is associated with SDV. However, eve with 100% SDV beig performed, barely 3-5% of the data is really subject to chage. A phase II trial coducted uder a US IND applicatio i 2011, demostrated that cetralized risk-based moitorig, coupled with Direct Data Etry (DDE) ito a e Cliical Trial Record (ectr), similar to a EMR, followed by the data beig directly pulled ito the EDC database, practically elimiates the eed for SDV. A web-based pdf file was geerated, which was the viewed i a read-oly ectr viewer which serves as a trusted third party eviromet. The results were idicative of faster database lock timelies, higher data itegrity as miimal trascriptio is ivolved ad a reductio i the moitorig effort to the order of 50% to 60%. 5

6 EDC Evolvig Perspectives It is also expected that more tha 50% data will flow from alterative sources such as labs, device data, ECGs, scaers, or get pulled i from EHRs. Thus, appropriate goverace eeds to be established to esure data itegrity ad appropriate data flows. The advatages of viewig data i real time, the beefits of rollig locks allowig for the provisio of iterim data for data safety moitorig boards, iterim reviews, or submissio, ad the eed for real-time data isights to support the icreasig umber of adaptive trials to allow for dyamic mid-trial modificatios i study desig, have resulted i over 50% of the idustry usig EDC solutios today. That beig said, the cost beefits have t traslated as plaed, as trials become icreasigly global ad ivolve multiple stakeholders; with this the added o user licese costs ad the 24/7 helpdesk support costs (across multiple laguages) have ofte bee prohibitive. I additio, for large pharmaceutical compaies with studies ruig simultaeously, the impact of a techical glitch stallig all trials for some time is mid bogglig. The depedecy o capable IT support ad the eed for a techologically fluet user base are also critical to the success of EDC deploymet. The value of this tool is lower whe coductig phase I studies, as agaist phase II-IV studies. Further, EDC is ot always the most cost effective solutio for smaller players owig to the overall cost implicatios. Hece, while most compaies are either there or are makig a coscious effort to adopt EDC, oe must take cogizace of the costs ad the associated risks as well. The Future Visio It s About Trasformatio We foresee a shift from a FSP approach, where specific activities withi the data maagemet life cycle are outsourced, to a ed-to-ed outsourcig approach, where sposors are lookig for a oe-stop shop. I additio, sposors are lookig at vedors who ca also provide the IT capability to cosolidate all their data, provide all the ecessary IT support, ad esure data security ad privacy. Pharmaceutical compaies are lookig for the ability to pick up all the data that has bee pulled i from multiple databases ad to map the same i a format that is Study Data Tabulatio Model SDTM compliat ad submissio ready. They are also lookig for tools that allow real-time visualizatio of reports ad data treds, ad GUIs that are extremely user-friedly ad accessible. The role of the data maager is also potetially evolvig to oe showig icreased owership of the quality of the data, as remote, risk-based moitorig seems ot so distat a visio. The passive data processor is trasformig ito a perso who ot oly is the first to see the data, but also remotely moitors data, idetifies treds ad issues, ad flags the eed for a limited umber of targeted site visits. Further, the data maager should be cogizat of idustry best practices as defied i the Good Cliical Data Maagemet Practices (GCDMP) a SCDM publicatio. The fudametal ability to perform data validatio or site moitorig has become a hygiee factor ad oe clearly eeds to evolve to a differet level to meet the eed of the day. 6

7 Coclusio As pharmaceutical compaies look ito the future, it is about adaptig to chagig techologies, busiess models, ad evolvig roles without losig sight of the associated risks. Icreasig complexities of studies, global teams parterig to reduce timelies ad maage costs, ehaced eeds for data security as persoalized medicie ad the use of e-source start comig ito the picture, are all factors impactig the way data will be maaged. A willigess to challege status quo ad to drive trasformatio, both i process ad i midset, is the eed of the day. 7

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