ACDM22 Programme
The Association for Clinical Data Management (ACDM) Annual Conference has been running for over 30 years. ACDM22 will take place in Edinburgh, Scotland. The Conference will be held at the Sheraton Grand Hotel from the 13th-15th March.
Pre-Conference: 13th March 2022
14:00 – 14:30 Registration
14:30 – 17:30 Exploring Edinburgh
18:00 – 19:00 Whisky Tasting / Networking
19:00 – 22:30 Networking Buffet & Drinks
Day 1: 14th March 2022
08:40 – 11:00 Registration & Exhibition
Demonstration Hour 1
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Abstract:
To meet the challenges of ever-increasing data volumes and industry pressures to deliver faster while maintaining high quality and without increasing cost, IQVIA Global Data Management (GDM) developed Real-Time Data Cleaning (RTDC), a strategy which leverages centralized clinical data in a data lake, standards managed in metadata repositories, and workflow technology to enable automation of our data flows and review processes.
In this session, we will demonstrate how we:
1. Enable automatic ingestion and validation of data sources as they are received
2. Define data cleaning checks connected to the data sources
3. Automatically identify issues for review and action
4. Digitally route issues for resolution
5. Track and manage data cleaning
Presenter Details:
Elisabeth Condron (Senior Data Team Lead, Clinical Data Management, IQVIA)
Elisabeth has over 15 years’ experience and currently employed as a Senior Data Team Lead in IQVIA leading the Data Management team in ensuring that all Clinical Data Management duties are performed to required quality standards. Her main duties and responsibilities consists of coordination of all DM activities including all aspects of collection, validation and cleaning of clinical trials data. In addition she is also responsible for managing external vendor data. Having started out on paper studies, she has witnessed many changes in how the day to day conduct of Clinical Data Management is performed.
She looks forward to demonstrating the next leap in the transformation of cleaning patient data at ACDM.
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Demonstration Hour 2
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Abstract:
TBA
Presenter Details:
Sverre Bengtsson (Co-Founder, Sr VP Strategic Relations, Viedoc)
Sverre Bengtsson started working as a statistician and data manager in the mid 90’s with probably the world’s first ePRO Minidoc. Minidoc was a perceived as a very user friendly and portable patient diary (as they were called then) and it was praised by the users for it’s high tech interface, it was so small and light weight. It weighed approximately 1 kg (2 lbs) and had four buttons where you could give your answer to multiple choice questions. Imagine this today!
Sverre worked for many years in data management for all kinds of paper CRF trials, the largest one had over 11,000 patients which needed massive amounts of binders and file cabinets. In the late 90’s Sverre managed his first global remote trial and used a more proper remote trial software in 2001.
In 2003 Sverre co-founded Pharma Consulting Group, a CRO who developed Viedoc EDC, where he has since focused on the business side. The CRO was later sold and he now focuses on Viedoc Technologies. Sverre has always been fascinated by the opportunities the e-clinical gives us. In 2011 Sverre co-founded the Swedish CRO association ASCRO. Sverre is active in many organisations within clinical research, including Eucrof, DIA and others.
Today, besides working at Viedoc, he sits on a number of boards and advisor roles.
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Up-Skilling Data Managers for the Future Panel
Presented by:
Maria Craze (Executive Director- Global Data Operations, Merck & Co., Inc. (USA))
Mike Jagielski (CEO & President, KCR)
Christopher Lamplugh (Associate Vice President, Global Data Management & Standards, Merck & Co., Inc. (USA))
Catherine Celingant (Senior Director, Data Management & Monitoring, Pfizer Inc.)
Jennifer Duff (Senior Partner, Watson Health Consulting for Life Sciences at IBM)
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Abstract:
The days of the traditional data manager of the past, manually entering data from a paper CRF into a database and passing that data along for another data manager to manually clean, are LONG GONE. Today, most see the data manager as a processor of the clinical data in an EDC system; turning clinical requirements into specifications, verifying edit checks, running exception reports and listings, etc. to clean the data and manually writing queries to site staff. Then stop and repeat. But I pose that even this role of the data manager is becoming obsolete and is the new definition of the “past” when describing a data manager. The role of the data manager is evolving, and we can catch up and stay ahead, or get lost in the past. Data Managers will have to think more intelligently and handle more complex scenarios as automation takes care of the repeatable and predictable. The Future data manager must be highly skilled in end-to end study design, signal detection, risk management, problem solving and team leadership as well as have a high tolerance for the ambiguous and live and breathe adaptability. We must recruit data managers for their POTENTIAL in these areas, cultivate that potential and develop the data managers for the future. Traditional activity-based learning plans and sequential development plans just do not evolve fast enough. In this session, the panel of CDM experts will provide their perspectives on the past, present and most importantly the future of the data manager. This must be a CONTINUAL EVOLUTION and never again a once and done catch up exercise. Just as the science and technology of clinical trials is evolving so must the data manager.
Learning Objective 1: Receive opinions and experiencial information from the experts in the CDM industry around the evoluation of CDM as a professiona dn industry.
Learning Objective 2: Receive advice and perspectives from respected highly experienced leaders in the CDM industry around the upskilling needs of the CDM of the future.
Learning Objective 3: Learn more about how the people working in CDM are an integral part of shaping the future.
Presenter Details:
Maria Craze (Executive Director- Global Data Operations, Merck & Co., Inc. (USA))
Currently the Head/Executive Director of Global Data Operations @ Merck & Co., Inc. (New Jersey, USA). Global Data Operations is a team of over 800 staff responsible for effectively and efficiently providing data collection and validation tool specifications, UAT of those tools as well as the in life data validation of all late stage clinical trial data.
Maria’s career at Merck & CO., Inc. (NJ, USA) started over 18 years ago in the data entry department. Over this career Maria has held many CDM roles ranging from CDM to lead CDM, Project Manager to Subject matter expert as well as several leadership roles.
Maria also serves the Pharma industry in the area of CDM by contributing to many conferences, organizations and committees. Maria is currently on the Board of Trustees of the SCDM and participates in DIA and eClinical Forum. She is a repeat presenter at ACDM as well.
Mike Jagielski (CEO & President, KCR)
Mike Jagielski is President & CEO of KCR, a contract research organization operating internationally. KCR is a mid-size full service CRO with 500 employees. He plays a significant role in advocating for a patient-centric approach in clinical studies. Mr. Mike Jagielski stepped in as President and CEO of KCR in 2013. He has over 20 years of experience in the global clinical trial operations industry. Prior to joining KCR, Mr. Jagielski worked for Merck & Co, Inc. (NJ, USA) for over 13 years, holding managerial positions across many different countries and regions.
Christopher Lamplugh (Associate Vice President, Global Data Management & Standards, Merck & Co., Inc. (USA))
Christopher Lamplugh is the Associate Vice President and Head of Global Data Management & Standards @ Merck & Co., Inc. (New Jersey, USA) providing Clinical Data Management Services for both early and late stage trials, including data standards, IRT, COA, PV Case Processing, and other technical business enablement responsibilities. He has been in multiple leadership roles throughout his 16 year career @ Merck & Co., Inc. (NJ, USA). Chris has also led the creation, expansion and operationalization of MSD’s Data Management Center Model across numerous locations. Prior to his CDM career, Chris worked for General Electric for a decade in the area of Sales Management and Sales Force Effectiveness and Quality. Chris is a Certified Six Sigma Black Belt and is active in several other industry forums as well; such as, SCDM, DIA and multiple user groups and professional working groups.
Catherine Celingant (Senior Director, Data Management & Monitoring, Pfizer Inc.)
Catherine Celingant celebrates 30+ years in the Pharma/ Clinical Research Industry. Her experience ranges from Data Analyst, Manager, Director and Senior Director across several influential companies; such as, Millennium (Takeda), Genetics Institute (Wyeth) and Accenture. Catherine is currently a Senior Director @ Pfizer, Inc. in Data Management & Monitoring; an integral delivery unit within the Global Clinical Trial Execution organization, responsible for timely and high quality data management deliverables.Catherina is a member and participant in many industry forums and teams; including efforts by Transcelerate, eCLinical Forum, SCDM and PhRMA EDC. She has presented in such forums as SCDM, DIA, SCOPE and PhRMA (just to name a few).
Jennifer Duff (Senior Partner, Watson Health Consulting for Life Sciences at IBM)
Jennifer is the Vice President/Senior Partner leading the Watson Health eClinical and Client Solutions, and Consulting businesses for the Life Sciences practice at IBM. I am responsible for bringing the power of IBM Watson Health advisory services and IBM solutions to the Life Sciences industry, as well as shaping and leading the eClinical and Life Sciences Client Solutions business strategy and growth of Watson Health Life Sciences. I have over 23 years of experience in the Life Sciences industry with specialization in enabling and scaling industry-leading services and technology solutions for pharma and biotech clients. I believe in the need to challenge industry norms and seek powerful, novel solutions that drive business growth and deliver improved outcomes for Life Sciences clients and the patients they serve.
I also serve on the Chester County Workforce Development Board. Through my work with the Board, I am actively engaged in supporting Chester County residents and businesses. I have an undergraduate degree in biology and an MBA in biotech and healthcare management.
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12:45 – 13:45 Lunch & Exhibition
Embracing the SDTM mindset at Study Start to mitigate compliance issues
Presented by:
Els Janssens (Executive Manager Secure Data Office, SGS Health Science)
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Abstract:
Nowadays, it is impossible to imagine clinical research without the existence of the CDISC SDTM data standards which enable us to create structured, aligned, transparent, and comprehensive databases from raw data. Creating such CDISC SDTM compliant databases is crucial for statistical analysis and regulatory submissions. Especially with the evolution towards more complex study data, adaptive or innovative study designs and the pressure on shortening of study timelines, SDTM compliance is often considered to be quite challenging.
The success of SDTM compliance heavily relies on the quality of the protocol, study design, and data collection tools. Too often, focus on creating CDISC SDTM compliant databases is only initiated after finalization of protocol and EDC system. This may lead to delays in timelines, budget updates, and team frustrations when the SDTM mapping can’t be done correctly, or important data is lacking in the EDC study design. It is therefore important to proactively identify and mitigate these risks as part of a risk-based quality data management approach.
The presentation will discuss real-life examples where SDTM compliance issues could have easily been avoided by embracing the SDTM mindset from the start. These examples will emphasize that it is important to include someone with SDTM knowledge whenever documents, essential for data collection are being created. While standardization of data collection can be considered as an indispensable tool in creating SDTM compliant databases, the SDTM mindset should be the common thread from study start to end in the pursuit of success.
Since a Clinical Data Manager is heavily involved in study set-ups, they are well placed to contribute to this success by expanding their current skillset and act as key stakeholders in SDTM compliance issue mitigation.
Learning Objective 1: Understand that decisions made at study set-up can have a large impact on all downstream processes, in this case SDTM compliance.
Learning Objective 2: Value the advantages of adopting the SDTM mindset as an end-to-end approach and realize that risk-based quality data management, especially the Quality by Design approach (in protocol writing, study design, data collection, vendor data) is key for SDTM compliant databases and that these risks can be mitigated upfront.
Learning Objective 3: Identify common mistakes/pitfalls in protocol and EDC design that have an impact on the SDTM compliance of your clinical database – easy wins in practice.
Presenter Details:
Els Janssens (Executive Manager Secure Data Office, SGS Health Science) Els Janssens has more than 9 years of experience in the field of Clinical Data Management. She joined SGS Health Science in 2012 as Clinical Data Manager and later Clinical Data Manager Coordinator. After that she gained experience at the sponsor’s side overseeing DM CRO activities. In 2021 she returned to SGS Health Science in the function of DM Data Standards and Process Manager. In this current role she acts as cross-departemental DM expert, sponsor liaison and point of contact regarding DM data standards and processes, including SDTM standards. Els also provides support to the DM teams and business development activities with focus on process improvements.
Els holds a master’s degree in Industrial Sciences: Biochemistry, a master’s degree in Cellular Biotechnology and a PhD in Biomedical Sciences. [/bg_collapse]
Towards automated data cleaning: a process for the auto-detection of data anomalies and inconsistencies.
Presented by:
Jennifer Bradford (Director, Data Science, PHASTAR)
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Abstract:
We are at the start of what is likely to be a rapid evolution within data management; early steps towards embracing technologies which will provide overall efficiency gains in terms of cost as well as faster high-quality data to support analyses. These processes require effective collaboration between human and machine; both in the design and integration into existing processes and in the effective and successful application to data management activities.
In this session we will describe how PHASTAR is developing a guided-review approach to data cleaning activities. Through the application of AI and rule-based approaches we will demonstrate how, working closely with the study experts, the machine can auto-detect potential data inconsistencies and anomalies. We explore the potential efficiency gains from such an approach, the vital role of the human expert, particularly where free text is involved, and the progress and challenges integrating such a method into the existing data query process.
Although early days, we will outline the first steps towards an automated system as we look to build the foundations of a system that ultimately will learn, through expert feedback, how to identify data anomalies – providing a mechanism to drive increased time and cost efficiencies and empowering data managers to use such technology to their advantage.
Learning Objective 1: How AI can effectively be applied to clinical meta-data
Learning Objective 2: Understand potential areas for efficiency gains in data management
Learning Objective 3: Understand the interplay between human expert and machine in the application of advanced analytics
Presenter Details:
Jennifer Bradford (Director, Data Science, PHASTAR) Jennifer is Director of Data Science for PHASTAR leading and driving the delivery of innovative data science solutions. Prior to joining PHASTAR she worked in various data science and informatics roles across academia and large pharma. Jennifer earned a Masters and PhD in Bioinformatics from the University of Leeds University UK and a degree in Biomedical Sciences from the University of Keele, UK. [/bg_collapse]
Implementing and maintaining a successful CRF Standards Library
Presented by:
Andrew Gebbie (Senior Solution Consultant, Veeva)
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Abstract:
Working with eCRF standards produces numerous benefits yet few organizations maintain them as well as they’d like. Success is not determined by the size of the organization, but rather the ability to create, implement, and most importantly, uphold them.
This session provides best practices, checklists, and case studies for creating and maintaining a library of data collection standards. From creation and implementation to governance processes, attendees walk away with actionable insights to leverage with their own organization.
Learning Objective 1: Understand what to standardize
Learning Objective 2: Ensure alignment with key stakeholders
Learning Objective 3: Maintain and govern standards over time, Reduce database build and data cleaning cycle times
Presenter Details:
Andrew Gebbie (Senior Solution Consultant, Veeva) Andrew has worked in the Clinical Trials Arena for 30 years in both Data Management and Clinical Operations as well as Clinical Trails Software. After graduating from Glasgow Caledonian University with a B.Sc. in Applied Biology, Andrew joined a small CRO in Scotland that were later acquired by PPD. Starting off in Data Management then moving on to Database Building and Programming. The acquisition by PPD opened up new opportunities and this allowed Andrew to spend a few years as a CRA before moving back to Data Management in a Senior Management role. After 20 years with PPD, Andrew moved on to Solution Consulting and spent 9 years at Medidata. Andrew joined the Clinical Solution Consulting group at Veeva in 2020. [/bg_collapse]
New and emerging technologies: Navigating AHEAD to the future
Presented by:
Jesika Vora (Business Domain Expert – Lifesciences and R&D, Artificial Intelligence and Analytics, Cognizant)
Prabha Mishra (Functional Architect/SME – Artificial Intelligence and Analytics, Cognizant)
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Abstract:
Global spending on technologies and services that allow digital transformation is expected to hit £1.8 trillion, with businesses everywhere recognizing that they need technology to remain relevant, enhance efficiency and boost profitability. In order to enhance their business processes and provide improved value, modern companies are increasingly dependent on emerging technology, such as the Robotic & Intelligent Process Automation, Natural Language Processing and Generation, Big Data, Artificial Intelligence and Machine learning, blockchain and data analytics and it is no different for the Pharmaceutical and clinical development domain.
There are some known used cases for using real-world data, predictive analytics can help set up theories that can be tested by prospective investigations, probably increasing their success rate.
AI may fundamentally change the conduct of clinical studies. This involves forecasting enrolment and enhancing the recognition of center of study. Data analytics helps better specified groups of patients to develop precision-targeted treatments that improve success rates. Better insights and forecast can be generated and trial designs adapted and optimized by evaluating data over time and using real-world data. Performance can be enhanced by modular trials, and drugs may well be approved sooner, since tailored trials enable smaller samples of patients.
With increasing application of AI and data analytics with the clinical research domain, and there is a compelling need to explore its application across each phase of clinical data management as well. How can Robotic process automation, Natural language processing and generation, predictive analytics help in the entire lifecycle of a clinical study. A look at these new and emerging technologies which can help us work towards making the pharmaceutical industry from being into “early mature” phase of using these digital business technologies to “matured” phase.
Learning Objective 1: Transforming Study Start up using emerging technologies
Learning Objective 2: Application of new technologies during study conduct and close out
Learning Objective 3:
Presenter Details:
Jesika Vora (Business Domain Expert – Lifesciences and R&D, Artificial Intelligence and Analytics, Cognizant)
Jesika Vora, a pharmacy graduate with excellent academic records and additional certification in Master’s in Business Administration, currently working as a Business Consultant and Domain Expert in Artificial Intelligence and Analytics – Life Sciences domain.
Have an overall experience of 12.5+ years in Clinical Research and Data Management field.
Subject Matter Expert in CDM for the Cardio-Vascular and Respiratory therapeutic areas. Process trainer, Reviewer and author for SWI’s on Study Set-up and Conduct, SAE Reconciliation. Certified Six Sigma Green Belt, Business Analytics and Digital First Professional.
Experience in solution development and designing of Predictive Clinical Trial recruitment project and execution of AI assisted automated authoring workbench
Prabha Mishra (Functional Architect/SME – Artificial Intelligence and Analytics, Cognizant)
Prabha Mishra, a unique blend of bioinformatics, data analytics and computational science knowledge with extensive experience in biology. This has led her to foster elaborate multiple research projects management skills to support E2E drug discovery and development process.
15+ years of experience in preclinical and Clinical, RWE Research data handling, analysis and data mining
4 global Patents, 8 international paper publications, 12 international poster publication
Established many meta/Integrated/ Pooled data analysis pipeline for R&D especially (Biomarker, HTS DMPK, Toxicology, translational research)
Designed and executed various Clinical and preclinical Data Science projects viz. AI assisted advance automated authoring workbench, Semantic data model, RWE/RWD data usage in patient recruitment etc.
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14:45 – 15:15 Break & Exhibition
Interactive Think Tank Panel
Presented by:
Robert Nichols (Strategic eClinical Advisor to the Pharma Industry, NB Solutions)
Bill Byrom (VP, Product Intelligence and Positioning, Signant Health)
Derk Arts (CEO and Founder, Castor)
Philippa Waller (Head of Biometrics, MAC Clinical Research)
Alex Franklin (Project DM Director – Immuno-Oncology, GSK)
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Abstract:
There will be a highly interactive Think Tank session at this year’s conference. A panel of industry experts with a broad set of experiences will be available to take questions and provide insight into the rapidly changing world of the Data Manager. We welcome questions in advance to put to the panel as they help to make sense of diverse challenges including the shift to more decentralised trials, the need to put a diverse group of patients at the centre of research, the emergence of many new data sources including wearables, and the increased use of technology for all aspects of the trial.
Learning Objective 1: To understand different viewpoints on a wide range of topics that impact the role of the Data Manager
Learning Objective 2: Learn how different sectors (Pharma, CRO, Tech) have different perspectives on the same issues
Learning Objective 3: Challenge your own way of thinking about specific data management topics, and engage with an experienced panel
Presenter Details:
Robert Nichols (Strategic eClinical Advisor to the Pharma Industry, NB Solutions)
Rob has extensive experience of delivering high quality strategic solutions to the pharmaceutical industry while working in first-in-class global clinical technology companies and Contract Research Organisations (CRO), as well as 7 years in the public health research departments of world leading academic organisations. Subsequently he has taken the knowledge gained while working for large established companies and applied in start-up, scale-up, and fast-growing ones in the eClinical space (including eDC, RBM and eCOA specialist companies). He now works as an independent strategic advisor to pharma, CRO, and investment companies.
Bill Byrom (VP, Product Intelligence and Positioning, Signant Health)
Bill serves as Vice President at Signant Health. He has worked in the Pharmaceutical industry for 30 years and is a recognised leader in eClinical product strategy, eCOA and decentralized trials. Bill is an experienced scientific expert and the author of over 70 publications and two industry textbooks on electronic patient-reported outcomes (ePRO). His recent scientific work includes the use of wearable and sensor technology and bring-your-own-device (BYOD) eCOA in clinical trials. Bill provides independent eClinical commentary via LinkedIn (http://uk.linkedin.com/pub/bill-byrom/5/697/713) and Twitter (@billbyrom).
Derk Arts (CEO and Founder, Castor)
Derk Arts MD, PhD has 15+ years of experience in medicine, research and technology. He founded Castor to solve the biggest issues in clinical research: a lack of inclusivity, patient focus and impact of data. Castor enables sponsors worldwide to run patient-centric trials on a unified platform that helps them maximize the impact of research data on patient lives. Dr. Arts believes the key to achieving lasting change in the industry is through scalability and standardization.
Philippa Waller (Head of Biometrics, MAC Clinical Research)
Currently Head of Biometrics at MAC Clinical Research, Philippa has spent over 25 years driving the development and delivery of high-quality data within CROs with focus on ensuring Data Managers, Statisticians and Statistical Programmers have the right processes, systems and teams in place to allow them both to deliver to the best of their capabilities and to further develop those capabilities. A passionate leader and people manager, she takes huge pride in the development of individuals and teams with the high positive impact they consistently bring to the delivery of clinical trials.
Alex Franklin (Project DM Director – Immuno-Oncology, GSK)
I have over 20 years experience within the field of Clinical Data Management leading global studies from Phase I and through to Phase IV, within both a CRO and Pharmaceutical environment.
Over the last 10 years I have predominantly been the Data Management lead Oncology and Gene Therapy trials coordinating the end-to-end data management activities for an asset from commit to development through to submission. Most recently I have also been supporting the roll out of new data management tools and processes as well as supporting a number of different initiatives looking at standardisation and process improvements within the group.
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Demonstration Hour 3
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Abstract:
Accelerating Digital Trials with Best-in-Class Technology
In this ACDM22 Demo Hour, join eClinical Solutions and Formedix as they discuss how best-in-class technology can automate end-to-end clinical trials. The elluminate Clinical Data Cloud is the foundation of digital trials – a platform that streamlines the clinical data pipeline across all data sources, from ingestion to insights. Integrations with best-of-breed technologies such as Formedix ryze Clinical MDR maximize speed, quality and efficiencies. This session will use real-world use cases and live demonstrations to explain the business benefits of CDR (clinical data repository) and MDR (metadata repository) integrations. See how fully developed interoperable systems work in harmony to drive long-term ROI in today’s increasingly complex data environment.
Presenter Details:
Achilles Zaras (Solutions Consultant, eClinical Solutions)
Achilleas has 14+ years of experience in the software industry which involves providing Clinical Data Hub solutions for Pharmaceutical companies and biotech’s, managing software development teams, hands-on coding in Microsoft .Net platform as well as Business Intelligence Suites like QlikSense. Having enjoyed a progressive career in diverse roles including responsibilities of a Solutions Consultant, Team Manager, Software Engineer and Business Intelligence Analyst in various sectors like Banking, Retail and now the Pharmaceutical industry.
Gilbert Hunter (Customer Success Manager, Formedix)
Gilbert joined Formedix over seven years ago as a Technical Writer. Four years ago, the knowledge gained from content development together with his customer service skills marked him out for transition to the Professional Services Team. In his current role, Gilbert provides CDISC and software training, support and consultancy services to Pharmaceutical, Biotechnology and CRO organisations. He helps them save time and money by making their clinical trial design and regulatory submissions more efficient.
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Demonstration Hour 4
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Abstract:
Building the next generation of eCRF, ePRO / eCOA software using Arone EDC
Learn how the use of the new technology provided by Arone EDC enables faster implementation of modern platforms for clinical data collection in your clinical trials.
These platforms, known as eCRFs or ePROs, allow patient data to be collected and managed directly in a secure cloud environment.
Our Arone EDC platform is available on any desktop or mobile device, and can be used with or without an internet connection, allowing patient data to be collected anywhere and at anytime. You can also quickly and easily create or modify your clinical study follow-up questionnaires in an intuitive and no-code interface using our natively integrated form builder Arone Studio.
In addition to ensuring better data quality, they also allow clinical research professionals to consult and monitor data in real time within the study database.
Presenter Details:
Emmanuel Pène (CEO, Arone)
Emmanuel Pène is a French entrepreneur with more than 25 years of experience in the software industry. With a strong background in the sector of B2B software, but also in chemicals and pharmaceuticals, notably at Rhone-Poulenc Rorer, he took over in 2019 the management of Arone, a French software editor dedicated to the collection and management of patient data in clinical research, with the aim to bring software innovation to clinical studies.
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18:30 Close of Day 1
CONFERENCE DINNER & NETWORKING EVENT SPONSOR: PHASTAR
AWARDS SPONSOR: SGS Health Science
View the Award Winners and Runners-Up Here
Day 2: 15th March 2022
How data management can bring down submission timelines
Presented by:
Steven Benham (Professional Services Manager, Formedix)
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Abstract:
Clinical trials require the submission of many different types of participant data, and metadata, in multiple specified formats. Thousands of files must be transformed into analyzable data sets, in order for new medicines to be appraised for safety and efficacy, and to pave the way for regulatory approval. The trouble is, when data submission requirements are left to be dealt with at the end of a clinical trial, this can cause huge delays and adversely impact submission timescales.
However, there are steps that can be taken to address and reduce this risk. This presentation will discuss the various ways organizations can reduce submission timelines to
authorities such as the FDA, and indeed, how they can actively speed up the submission process and help get drugs to market faster.
The audience will learn how designing datasets upfront – in conjunction with form design – is the key to avoiding errors, issues and delays downstream at submission.
For example, we will discuss how using the correct Controlled Terminology and CDISC SDTM compliant forms and datasets at design stage, sets you up for smoother and faster SDTM mappings. When your forms and datasets comply with standards upfront, you avoid having code terms that don’t map to SDTM at the end of the trial. And you don’t waste time trying to interpret and correct mappings when your priority is submission.
Participants will also hear how standardization across the clinical trial lifecycle can be leveraged to reduce submission timelines. For example, how standardized content can accelerate dataset generation. And how continual validation of content and monitoring against CDISC SDTM standards is integral to reducing, and in fact expediting clinical trial submission timescales.
Learning Objective 1: How to avoid delays downstream in the submission process.
Learning Objective 2: How to speed up the submission process and get drugs to market faster.
Learning Objective 3: How upfront compliance with standards can positively impact submission timescales.
Presenter Details:
Steven Benham (Professional Services Manager, Formedix) Steven Benham has been with Formedix for over 4 years. Starting originally as a Solutions Consultant, he worked to author and present Formedix training courses for SEND, SDTM, Define-XML, ODM-XML, Define-XML and Dataset-XML. He has also been involved in a number of clinical data programming projects helping to deliver in Interim Analysis (IA) SDTM and FDA SDTM clinical submissions. He is now the Professional Services Manager and currently oversees all Formedix clients. [/bg_collapse]
The expanding role of Real World Data in the drug development process
Presented by:
Danielle Grindley (Real World Data Manager, Bionical Emas)
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Abstract:
Real World Data (RWD) encompasses all health data collected outside a randomised trial and can include patient-reported outcomes (PRO), registries, early access programs, billing information, Electronic Health Records, social media, and electronic devices.
Traditionally drug development focused on Randomised Controlled Trials (RCTs) for assessing the effectiveness of a new drug or intervention. However, due to the increase in technology and patient centricity throughout the clinical research process and the increasing acceptance of Real World Data by regulatory authorities, the role of clinical data management is evolving. This presentation will focus on the use of RWD within the drug development process and how clinical data management can improve the validity and reliability of RWD programs.
Early Access programs are becoming an invaluable opportunity to collect data on patients treated with an unlicensed medication outside a clinical trial setting. RCT’s have strict eligibility criteria, which can reduce the generalisability of results within the general population. The collection of patient-reported outcomes, either through paper or electronic devices, can provide vital information regarding the effectiveness of a drug from a patient’s perspective. Alongside, patient registries can help understand the burden of disease and the current standard of care offered to specific patient groups.
The quality of RWD is often questioned due to the lack of reproducibility and controls. Furthermore, clinical assessments in routine clinical practice can differ significantly from those collected in RCT’s. Clinical data management can aid in increasing the validity of the results within an RWD program. The design of endpoints to match assessments collected in routine clinical practice and a clear protocol, alongside a monitoring plan, can reduce bias and improve reliability. The correct implementation of analytic tools throughout the program can highlight any potential issues for further investigation and reduce problems at analysis.
Learning Objective 1: What is Real World Data
Learning Objective 2: Uses of RWD within the drug development process
Learning Objective 3: Role of Clinical Data Management in improving RWD programs
Presenter Details:
Danielle Grindley (Real World Data Manager, Bionical Emas) Danielle Grindley currently works at Bionical Emas, the only CRO to combine Clinical Development, Early Access Programs and Clinical Trial Supply as a Real World Data Manager. She has a degree in Biomedical Science and a Postgraduate Diploma in Public Health. Danielle started her career as a Clinical Data manager within the NHS, primarily focused on paediatric observational studies before moving to the Institute of Cancer Research to work in clinical trials. She now combines her experience in the Clinical Data Management of randomised clinical trials and Observational studies to work exclusively on real world data programs. [/bg_collapse]
Update from ACDM Data Management Expert Groups
Annual General Meeting of the Association for Clinical Data Management
11:00 – 11:30 Coffee & Exhibition
Data Integration: How best to perform data management activities on data from multiple external sources
Presented by:
Rashida Rampurawala (Manager – Study Data Management, GSK)
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Abstract:
Data integration has played an imperative role in the evolution of data management over the years. For the longest time, instream data collection on CRF was done by manual data entry and the external data came in as transfers. Industry has made a pragmatic shift towards data sciences/analytics and data integration had been a constitutive part of this shift. The need of the hour is to have a well-defined strategy on handling data coming instream into the database from multiple external sources via integration. Data Integration is pivotal as it consolidates data in an organized manner within the database which accelerates efficient research analysis. Below are the critical points encircling the “What, Why and How” of handling integrated data that DM team needs to factor in.
What? – DM translating protocol specification into data elements and to data points to be part of instream data via which integration
What? – Mapping of data, the integrated data must fit in with the defined eCRF data points as per CDISC/set standards.
Why? – Compatibility between EDC and various data integration tools. Check on EDC readiness for data integration, challenges/limitations etc.
Why? – Time, cost and effort of data integration from multiple sources.
How? – Perform Risk mitigation on downtime of the EDC if any, when data integration takes place from multiple sources. Is there any cross impact due to
multiple integrations?
How? – Mindful of how the postproduction update to the 3rd party tool impact the integration set up within EDC and vice versa.
How? – Efficient way of performing data validation activities on the integrated data. Checks to be performed at the EDC level or at the level of 3rd party
tool and how are the discrepancies managed? Should one eCRF have data integrated from multiple sources?
What? – DBL challenges – Do’s/Don’ts?
Learning Objective 1: To get the insights of what goes in terms of DM planning and activities prior, during and after the Integration set up from multiple external sources and how to improvise and optimize the same.
Learning Objective 2: How DM can further evolve and streamline the DM activities pertaining to handling data from multiple data integration sources.
Learning Objective 3: Addressing challenges, limitation of handling integrated data from multiple external sources.
Presenter Details:
Rashida Rampurawala (Manager – Study Data Management, GSK) Rashida recently completed her executive MBA from XLRI (top business school of Asia) and has done MSc Biomedical Science from University of East London (London, UK). She has been within clinical data management (CDM) since 2009 and is currently working in the capacity of Manager – Study data management at GSK . She started her career in UK and then continued back in India. She has 11 plus years of CDM experience and has presented at various conferences held by SCDM, DIA, ISCR, PHUSE and conducted RBM workshop at DIA and ISCR. She is a data visualization enthusiast and recently learnt the tableau tool and got hands-on experience on R programming too. She has worked as a study start up SME at one of her previous organization. She was also heavily involved at global level DM specific trainings too. Currently she is a part of the SCDM author group which is working on updating the GCDMP chapters for the CCDM certification. [/bg_collapse]
Predictive Analytics amplifies the scope from “Just” Managing to Curating Clinical Data
Presented by:
Hari Priya (Senior Clinical Data Science Lead, Merck KGaA)
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Abstract:
Introduction: The main objective of this abstract is to provide a forward‐looking and pragmatic view on how predictive analytics help in the emerging role of clinical data mangers from simply managing and analysing data, to proactively predict the trial outcomes by being more investigative, using metrics and predictive analytics.
Since the predictive models are created based on the patient population and treatment design of the trial, each predictive model is unique for a certain study. When predictive analytics is combined with machine learning capabilities, it enables data mangers to curate the data from multiple sources, for example, information from public health records and historical trials can be utilized to select the patient population for the upcoming trials and to develop studies that will generate statistically significant results.
Few of the important benefits of using predictive analytics are:
• “Time saving” and focus on the cleaning of subjects that will be part of the analysis.
• It can help in identifying the subjects, that may develop potential AEs and what percentage of AEs could later become SAEs based on the demographic information of the subjects and medical history.
• It’s possible to predict the early withdrawals subjects and identify data patterns to drive better data outcomes.
• Identification of fraudulent activity in the trial like alteration of eCOA scores.
• Identification of the sites that have had under-reporting of AEs, explaining why few of the sites have high number of unscheduled visits.
What are the tools used in predictive modelling?
Some of the tools, that are used to predict data or for data cascading are – Power BI, JMP, Tableau, KNIME & Spotfire.
Conclusion: These data-driven approaches add value, save resource, focus on patients for the analysis, thus improve patient experience, enable faster regulatory approvals and provide early access to treatments.
Learning Objective 1: What is predictive analytics and its benefits?
Learning Objective 2: How could we leverage predictive analytics in clinical data management and know about the tools used in predictive modelling?
Learning Objective 3: How can predictive analytics empower the clinical data managers to emerge into the role of clinical data scientists?
Presenter Details:
Hari Priya (Senior Clinical Data Science Lead, Merck KGaA) Priya started her career in Clinical Data Management for a little more than 12 years ago. She has held a variety of positions at Pharmaceutical companies, CROs and Pharma BPO&Consulting, with increasing responsibility that expands to SDTM & Clinical Data Analytics. In the recent past, she led an initiative to develop strategies for future roles in Clinical Data Sciences. She is associated with various volunteer organizations like CDISC and Pinnacle21 wherein she is actively involved in creating clinical data standards and ensuring that submission data is compliant to regulatory agencies . With her ongoing contribution in developing the Data Decision Metrics and Analytics she was identified as Co-Lead for “CDM Metrics & Analytics” DMEG at ACDM.
She is an active Conference Committee member and conducts hot topic discussions, webinars and manages newsletters and publications. [/bg_collapse]
From Siloed to Streamlined: The Convergence of Roles in Data Management, Operations, Monitoring and More
Presented by:
Dawn Kaminski (Senior Director, Data Strategies, eClinical Solutions)
Graham Craig (Data Management Therapy Area Head, GSK)
Jason Gubb (Global Clinical Operations Consultant and Co-founder of Emergent Teams, Consultant)
Panikos Christofi (Director of Product, Science 37)
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Abstract:
Clinical Data Management, Clinical Operations, Monitoring and Biostatistics were traditionally seen in the industry as separate and distinct functions. But the past few years have revealed a shift and overlap in these roles. The overlap in traditional roles has been brought on in part by developments in the handling of clinical data and the ability to find meaning from the vast volumes of data being collected in trials today, a change that is only being accelerated by Decentralized Clinical Trial (DCT) model adoption. We are hearing that “traditional” methods simply won’t scale in this new paradigm. Data management has begun to focus more on agility and flexibility, prioritizing quality by design and focused data review that is enabled by tech. In Clin Ops, there is increased emphasis on advanced analytics to highlight where attention is needed most, monitor and spot trends. There is a merging of processes happening, but the consistent theme unifying the functions is that of risk-based approaches .
This panel will bring an expert Data Management perspective together with representation from other functions to discuss how Operations, Monitoring and Biostatistics roles have evolved, and where they now overlap. Is a new discipline emerging from this shift and what does that look like? The group will examine how to leverage this new RBQM paradigm to strengthen clinical development, and address what new technologies, techniques and skill-sets are needed to best align teams in this new model.
Learning Objective 1: Identify the overlaps in the data management, operations, monitoring and biostatistics functions – where is this being shown and why?
Learning Objective 2: Address how risk-based approaches are part of this shift and what it means for industry.
Learning Objective 3: Discover the skill-sets, process changes and technologies that can be leveraged as part of this new model.
Presenter Details:
Dawn Kaminski (Senior Director, Data Strategies, eClinical Solutions) Dawn has over 20 years of experience in the pharmaceutical industry. She have worked within every level of clinical data management, from Data Coordinator to Senior Director where she participated in or had oversight for more than 250 clinical trials. During her time in the industry, she has provided consultation to organizations on clinical trial conduct, best practices in Data Management and data capture as well as developed standardized libraries and templates to support the adoption of CDISC standards. She is an active member of SCDM as a GCDMP SME, course designer and webinar presenter as well as Co-Chair of the annual conference (2018-2021) and will serve on the SCDM Board of Trustees beginning in 2022. Dawn is involved as a member of the CDISC-CDASH core team, Diabetes sub-team, CDASH CFAST Expanded Leadership Team and former Co-Chair of the CRF Library project. Dawn currently holds the position of Senior Director, Data Strategies, where she supports business development as a Clinical Subject Matter Expert for both software and data services.
Graham Craig (Data Management Therapy Area Head, GSK) Graham has been working in Data Management for over 25 years growing an in-depth and diversified knowledge of the Industry. During his career Graham has held various management positions in CROs and Biotech’s before joining GSK in 2012. Graham has a passion for process simplification, challenging the design and conduct of clinical trials in order to drive efficiency and acceleration.
Jason Gubb (Global Clinical Operations Consultant and Co-founder of Emergent Teams, Consultant) Jason has over 25 years’ experience in Global Clinical Operations strategy and leadership. He has an applied knowledge of leveraging internal and external data, analytics, digital technology and collaborative partnerships to create actionable insights for study teams. Jason works with startups, pharma, vendors and CROs to develop innovative approaches to optimize protocol designs, modernise clinical trial conduct and accelerate trial delivery.
Panikos Christofi (Director of Product, Science 37) Panikos is the Director of Product at Science 37 with a focus on Connected Devices and Data. He has always sought to act as an ambassador to multiple disciplines, combining Clinical, Business and Technical expertise within the umbrella of Clinical Trials. Some topics of interest for Panikos are clinical data standardization, patient centricity, patient engagement and decentralized trials.
He started in the Clinical Space in 2011 as a Clinical Database developer combining a self-taught passion in Informatics with an educational background in Biosciences (Human Genetics).
After a time in software development, he transitioned to business analysis for a large CRO in a role focusing on clinical integrations and later on technical consultancy. This role allowed exposure to a large set of Clinical Systems, Clinical Standards and working practices across the industry. It was here that Panikos developed an interest in Clinical Data Standardization and how technology can support clinical and operational roles.
From there he moved to a Product Management role within the eCOA space where he further cultivated an interest in the use of connected devices within the clinical space.
Currently, Panikos is working within Science 37 to support the evolution of the Agile Clinical Trial through his work with Connected Devices and Data. [/bg_collapse]
eSource arising: clinical data automation possibilities beyond data capture
Presented by:
Sofie Stynen (Clinical Data Manager Coordinator, SGS Health Science)
Annelies Van Zeveren (Project Director Biometrics and Medical Safety & Regulatory, SGS Health Science)
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Abstract:
When implementing the 1st generation of eSource system at SGS, the focus was on facilitating data capture and converting clinical data directly to a Study Data Tabulation Model (SDTM), making eCRF redundant. After getting familiar with eSource, we are now ready to use our knowledge and expertise and take eSource clinical automation to the next level with the 2nd generation of eSource system.
This presentation will highlight our acquired insights and the challenges faced from both systems, resulting in improved efficiencies. The focus on standardized data and the use of code lists to convert easily to SDTM are key for efficiencies. With a proper test environment set up in the 2nd eSource system, it is now possible for data management to enter dummy data, making it easier to set up SDTM conversion. Data visualization and accessibility have improved significantly, and the new query management seems to allow for shorter data cleaning-timelines.
In order to keep improving, we are already thinking of other functionalities that could be explored in the 2nd eSource system. Future plans such as coding and handling of blinded data are being considered.
Learning Objective 1: Getting familiar with the eSource system as source electronic data capturing tool which can be used at the clinical pharmacology unit as source but also a tool to allow clinical data to be directly captured and converted to SDTM
Learning Objective 2: Understanding the advantages and challenges to implement such a system at a CPU for data management
Learning Objective 3: Importance of a good collaboration
Presenter Details:
Sofie Stynen (Clinical Data Manager Coordinator, SGS Health Science) Sofie holds a master’s degree in Communication Science. After graduating in 2008, she started at the SGS Clinical Pharmacology Unit in Antwerp as Clinical Trial Assistant (CTA). After gaining experience on site and becoming Team Leader of the CTA’s, it was time to start looking at data from a different perspective and Sofie started working as Clinical Data Manager at SGS Mechelen in 2015. In 2019 Sofie became Clinical Data Manager Coordinator and Site Matter Expert for eSource. In total she has more than 13 years of experience in clinical trials, specialized in Phase I trials.
Annelies Van Zeveren (Project Director Biometrics and Medical Safety & Regulatory, SGS Health Science) Annelies has over 10 years of experience in clinical research. She joined SGS Health Science, a Clinical Research Organization, in 2008 where she first worked as Clinical Data Manager and then later on as Project Manager Biometrics. In 2015, she became Project Director Biometrics and Medical Affairs at SGS. In this role she supports the business development, the marketing and biometric teams to increase client focus. She provides decisions and solutions how the clinical project objectives and client needs can be achieved. She is also responsible for providing strategic direction in assessment and implementation of process improvements, new technologies and innovations to increase the quality of biometric services. Annelies holds a master’s degree in biotechnology and a PhD in veterinary science from Ghent University in Belgium. [/bg_collapse]
The benefits, challenges & myths of DECENTRALISATION – from the lens of medical device industry
Presented by:
Vishal Kapoor (Group Manager, Data Sciences and Systems, Terumo)
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Abstract:
Decouple the clinical activities from physical location requires digitalization and pragmatic clinical plan. The primary focus should be on the innovative trail design and data collection methodologies. Patient centricity requires subject’s involvement in understanding their disease. The benefits of engaging subjects from their comfort zone should be coupled with the inclusion of technological platforms such as telehealth, eConsent, ePRO, eSource, wearables. The concept of mobile nursing is becoming a supportive pillar and complemented the initiative. Real time data & reporting enhances quick access to data for informed decisions. Unfortunately, many challenges must be overcome to reach the full potential. Intervention and Imaging are the initial hurdles where the challenge lies. Keeping patient away from site at all in long time span trial is a myth in virtual environment setup
Learning Objective 1: Understanding the concept of decentralisation
Learning Objective 2: Discuss the benefits and what are the technologies should we use to attain
Learning Objective 3: The downside or where we the challenges exit and how to overcome those challenges
Presenter Details:
Vishal Kapoor (Group Manager, Data Sciences and Systems, Terumo)
Vishal is leading clinical data science and systems within Medical and Clinical division at Terumo with keen focus on adding value in end to end Clinical data solutions & innovation. He has demonstrated his comprehensive expertise in strategies, infrastructure, data programming, standardization, processing & clinical systems (CTMS, eTMF, EDC) for about 14 years across various therapeutic areas in pharmaceutical (MSD), medical devices (Terumo) and IT services (HCL Tech). His rich experience in data solutions further fuels his passion for adopting new technologies like AI and big data to structure and solve clinical & medical aspects. Currently he is focusing on adapting virtual clinical trial methodologies and associated technologies.
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Complex & Innovative Trial Design – a deep dive into device driven data acquisition
Presented by:
Nina Christine Reyes Ráfales (Manager, Clinical Data Management, IQVIA)
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Abstract:
It is said that the economic success of product development is supported by three pillars: economy, technology, and design. This can be transferred one-to-one to our industry as well. Technology that moves forward at a rapid pace allows or forces us to rethink the design of our product And the design of our clinical trials.
We cannot move forward thinking of a trial design with one eCRF data source and only with vendor data added on. Device driven data acquisition is the method of choice for many trials already and it will be more and more in the future. The industry demands adaptive options supported by the trial design, to enable faster decision-making. The economy is demanding that we save money and time whilst being as effective and keeping the highest possible data quality standards. The fast-paced reality we are living in demands fast-paced solutions.
These new demands request a much more complex study design, with the ability of design to out-perform more traditional design types.
During the talk we will have a look at the benefits for the pharma and biotech companies and ultimately the patients. We’ll look at the key factors that drive success of a complex & innovative design and then do a deep dive into one of its main pillars to success; device driven data acquisition and how patient focused Drug development trends drive the demand for connected device solutions.
Additionally, the presentation will deal with the value of device driven data acquisition across the drug development lifecycle and give an overview on the most important devices for the device driven data acquisition used in clinical trials that are state of the art.
The goal of this interactive session is to “kidnap” the audience/participants to the new reality of clinical research and give a short oversight on the more innovative parts of the clinical trials with its external data possibilities and patient centric approach.
Learning Objective 1: Device Driven Data Acquisition – what it means
Learning Objective 2: Device Driven Data Acquisition – why we need it
Learning Objective 3: Device Driven Data Acquisition – best practice
Presenter Details:
Nina Christine Reyes Ráfales (Manager, Clinical Data Management, IQVIA) Nina Reyes is a former nurse and a studied Computer Scientist. She is working in the Clinical Data Management area of the Pharmaceutical Research industry for over 16 years and is still fascinated by human data, which enables researchers to bring miracles to patients and their families all over the world. Nina has solely worked on the CRO side of the business. Her bio encompasses companies like Icon plc, Labcorp Drug Development and now IQVIA. [/bg_collapse]
13:00 – 14:00 Lunch & Exhibition
AI and Data Management: Opportunities and challenges?
Presented by:
Tim Armitage (Executive Director, Business Solutions, ANJU Software)
Ashley Howard (Associate Director, Asset Lead, Pfizer)
Rich Davies (Vice President, CluePoints)
Sheelagh Aird (Senior Director, Data Operations, Phastar)
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Abstract:
Following the results of a questionnaire sent out to the ACDM members at the start of 2021 it is evident that many members and followers of ACDM are keen to understand more about how the application of artificial intelligence and machine learning will impact data management. The panellists in this session will discuss their perspectives around the opportunities and applications of AI for data management together with their perceived challenges, regulatory or otherwise, in the development and adoption of these technologies now and in the future.
Learning Objective 1: A better understanding of opportunities for AI/ML in DM
Learning Objective 2: An appreciation of the challenges surrounding AI/ML in DM
Learning Objective 3:
Presenter Details:
Tim Armitage (Executive Director, Business Solutions, ANJU Software)
An experienced technologist with over 30 years spent working with data across many different industry sectors across the globe. For the last 10 years, Tim has been working exclusively in the Healthcare and Life Sciences domain providing strategic advice and architecting technical solutions to help customers manage the volume and diversity of data collected through healthcare encounters and clinical research.
Tim joined Anju Software at the start of 2019 to provide support and guide Sponsors and CROs covering solution design, demonstration and technical help focussing on the eClinical and Data Intelligence suite of products.
Tim holds a Bachelor of Science degree in Applied Biology from University of Hertfordshire, UK and is currently studying for an MSc in Big Data and Data Analytics at the University of Liverpool, UK
Ashley Howard (Associate Director, Asset Lead, Pfizer)
An experienced data manager leader Ashley has worked across therapeutic area disciplines within both the pharmaceutical and CRO industries. With over 11 years’ experience in Clinical Data Management Ashley started his career in the late phase Data Management department at PAREXEL. He progressed into a Data Management operational leadership position where he had overall accountability, as an account lead, for the execution of the Data Management strategy on numerous complex Oncology studies.
Ashley joined the Oncology team within the Data Monitoring and Management department at Pfizer in 2018 and is currently an asset lead supporting the development of a number of key, pivotal compounds. Ashley is a business lead for Pfizer’s development and implementation of the Smart Data Query (SDQ) tool, an industry first leveraging AI/ML to hyper-accelerate complex data review and reconciliation activities.
Ashley holds a Bachelor of Science degree in Biology from Sheffield Hallam University, UK.
Rich Davies (Vice President, CluePoints)
Richard Davies joined CluePoints in September 2018 and is based in the UK. As VP, Solution Expert his role is to support organizations’ adopting CluePoints solutions from a technical, functional and business process perspective, particularly as they execute their vendor selection programs. Additionally he has product management responsibilities and provides a bridge between customers, prospects and ongoing product development. He has worked for technology vendors for overt 20 years but prior to this, he worked in data management with Fisons Pharmaceuticals and Astra. Richard graduated from DeMontfort University, Leicester, with a Bachelor Of Science degree in Computer Science.
Sheelagh Aird (Senior Director, Data Operations, Phastar)
With more than 30 years of experience in clinical data management, Sheelagh has directed and delivered projects in all phases of clinical trials across numerous therapeutic areas and data collection platforms. Sheelagh holds a BSc in pharmacology and doctorate in pharmacokinetics from the University of Bath. She has led PHASTAR’s Data Operations group since 2016.
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Who’s your data scientist? Does one shoe fit all?
Presented by:
Tanya du Plessis (Chief Data Strategist and Solutions Officer, Bioforum the Data Masters)
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Abstract:
It has largely been accepted that our industry has, or is in the process of, moving to data sciences. However, the journey encompasses more than just a title change or addition of a new job description. It requires additional technology/ability in data review/visibility and most importantly the understanding of (and approach to) data as an asset providing continuous insight and not just the “result’ of the clinical trial. Let’s talk about what makes data sciences different and if there are there any roadblocks or alarms we should be heading through our metamorphosis. This should be an exciting prospect, not a threatening one. It means a change in focus, adaption to new strategies and support of new technologies.
In this presentation I would like to discuss… the different technology approaches companies have taken. With an open budget the latest and greatest technology can be used, but for smaller companies without the budget there are some innovative ways to go about this change. Additionally, the different ways companies have already started adapting to this new chapter, what are the different approaches companies are taking, what they are planning ahead. Some companies have branched off of their central monitoring teams (which were already in place) to create a data focused team, others have combined the roles of central monitors and data analysts keeping their DM team as is, some others have combined analyst and scientist roles, and others have redefined new teams completely.
It will be great to discuss what works well in these models and where there are challenges, does one shoe fit all? And lastly it is important to understanding the opportunities this change brings for data managers, what current data managers can do now to prepare themselves.
Learning Objective 1: Why are we changing to data sciences
Learning Objective 2: How have different type sof comapnies made this change
Learning Objective 3: How and what can a data manager do to prepare
Presenter Details:
Tanya du Plessis (Chief Data Strategist and Solutions Officer, Bioforum the Data Masters) Tanya is currently Chief Data strategist and Solutions officer of Bioforum The Data Masters, she has 18 years industry experience. Leading various data management operation teams in innovative strategies for customized data delivery solutions, her dedication to optimal customer service/delivery is visible through long standing relationships. Ensuring she is always aware of the needs in operational delivery Tanya is also a certified clinical data manager (CCDM, SCDM) as well as a project management professional (certified PMP). [/bg_collapse]
Close of ACDM22 (passport competition & exhibitor prizes)
16:00 Close of ACDM21