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Matt Wilson guests the show and talks to Sam and Ivanna about how automating consent and recruitment processes can broaden the net in terms of the number of patients involved in clinical trials. A broader patient population means that underrepresented groups gain access to clinical trials and allow  a much more detailed characterization of an overall patient population.  

Removing barriers for patients to participate in trials also means using technology that is most accessible and sometimes low tech - such as the text message. Understanding your population can also help target your communication to specific groups, thereby increasing diversity in the trials participants. 

We speak about how Real World Data has evolved from databases over patient populations to electronic patient records and third party companies collecting large data sets. Using electronic health records directly means that the broken link between the actual patient and findings made in population level research is mended, meaning that the patients themselves can benefit directly from the findings in the large-scale studies. 

We also speak about the benefits of providing information to the patients about what their data has contributed to, and potentially providing them the benefits of the newly created knowledge. 

Matt encourages our industry to pursue open-mindedness to try and engage with new ideas and new ways of doing things. Not everything will work out, but the potential to unlock real value to patients is to great to ignore. 

“Patients want to help with research, and it is about providing them the means of doing that in a way that is not burdensome, and allow them to see how they have contributed. “
- Matt Wilson 

Notes

• Guest Matt Wilson : https://www.linkedin.com/in/drmattwilson/ 
• uMed: https://www.umed.io/ 
• Example mentioned of 23andMe: https://www.23andme.com/en-eu/?evr=epv 
• NHS Blood Donation Service: https://www.blood.co.uk/ 

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“It is always fun to have some data that makes you go Wow! I didn’t know this!” 
We speak to Ulla Sofie Lønberg and Helle Hartnack about whether men are risk takers and women reluctant to experiment with health technology, and if the only difference between the male and female physiology really is the ability to bear children.

We discuss the findings in a recent registry study about gender imbalance in the use of device-aided therapies. Unconscious bias may be at play for both patients, carers and physicians when selecting treatment, but also the roles that men and women typically play in society. 

We speak about how tailoring communication might make a difference, but also the need for behavioral clinical research. Adding the behavioral element to clinical research may just be the missing link in true patient centricity. 

We also speak about how mapping the non-patient journey may help understand the biases that exist in the system and how daring to differentiate your communication to patient groups may make it easier for the patients to make decisions about treatment.  

“I found that when we discussed these findings with people, we tend to get the same kind of comments. Either that men are risk-takers or men are tech-oriented and women are not. But what we discussed in this publication is that there’s actually very little data to support this notion. And if it is true that men are risk takers and women are not, should we just accept that?”

• Ulla Sofie Lønberg

Notes

• Guest Ulla Sofie Lønberg : https://www.linkedin.com/in/mdullasofielonberg/ 
• Guest Helle Hartnack: https://www.linkedin.com/in/helle-hartnack-0345352/ 
• Publication we speak about: Henriksen T, Dalhoff KP, Hansen HE, Brenneche AW, Lønberg US, Danielsen EH. Access and Use of Device-Aided Therapies for Parkinson’s Disease in Denmark. Mov Disord Clin Pract. 2020 Jul 2;7(6):656-663. doi: 10.1002/mdc3.12988.
• Invisible women: https://www.goodreads.com/book/show/41104077-invisible-women
• Device-aided therapies and Parkinson’s disease  

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Sam and Ivanna speak to Jakob Juul Rasmussen about the stubborn prevalence of paper in clinical trials, especially in small pharmaceutical and biotech companies. Paying money up front, covering the implementation and license costs and building up internal IT functions can be prohibitive for small pharmaceutical and biotech companies. This leads many companies to outsource their entire IT landscape to CROs. As a result, control over assets becomes complicated and cumbersome, as your clinical data risks being stored in different applications with multiple data models applied.  Standard configuration is helping bridge the gap, but compliance requirements from authorities for both internal and CRO-maintained software are unchanged. Jakob suggests a radical third way of getting the set of applications needed to run the business of any biotech or pharmaceutical company, without resorting to paper or complete outsourcing, transforming both how technology companies deliver IT solutions and how IT is anchored with the sponsor companies. 

“Small companies really want to focus on science and just have the necessary tools to provide the best science”

• Jakob Juul Rasmussen

Notes

• Guest Jakob Juul Rasmussen : https://www.linkedin.com/in/jakobjuulrasmussen/ 
• PharmaIT: https://pharmait.dk/ 
• ISPE GAMP 5 https://ispe.org/publications/guidance-documents/gamp-5 
• ALCOA ++ https://www.gmp-compliance.org/gmp-news/alcoa-what-does-it-mean 
• Pharmacovigilance Signal Detection: https://www.ema.europa.eu/en/human-regulatory/post-authorisation/pharmacovigilance/signal-management 
• EMA Notice to Sponsors on Validation and Qualification of Computerized Systems used for Clinical Trials: ​​https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/notice-sponsors-validation-qualification-computerised-systems-used-clinical-trials_en.pdfhttps://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/notice-sponsors-validation-qualification-computerised-systems-used-clinical-trials_en.pdf 
• DIA Reference models: https://www.diaglobal.org/en/resources/tools-and-downloads 

Technology mentioned

• Quality Management System (QMS)
• Electronic Trial Master File (eTMF)
• Electronic Case Report Form (eCRF)
• Regulatory Information Management System (RIMS)
• Box
• Dropbox
• SharePoint
• Teams
• Word 
• Electronic Signature 

Functions mentioned

• CROs 
•  IT

Abbreviations & Definitions

eCRF: Electronic Case Report Form

eTMF: Electronic Trial Master File

EDC: Electronic Data Capture

FDA: Food and Drug Administration 

QMS: Quality Management System

RIMS: Regulatory Information Manage

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Sam and Ivanna speak to Willie Muehlhausen about how simplifying and automating patient reported outcomes is not so much complicated, as it is complex. Willie shares his perspectives on the evolution of ePRO and eCOA and how the newer trend of decentralised clinical trials is closely tied to mastering the collection of patient reported outcomes. Willie is working towards making it possible to translate a clinical protocol into configuration in 12 minutes instead of 12 weeks and hints at other possibilities yet to be explored . If Willie could change one thing in our industry it would be increasing the level of knowledge sharing and knowledge retention. 

• Willie Muehlhausen  

• Guest Willie Muehlhausen
• eCOA Consortium (formerly known as the ePRO consortium) 
• Safira Clinical Research Limited 
• Recall Bias 
• CDISC
• ODM XML 
• Guidance on Ecological Momentary Assessment
• Considering BYOD in Clinical Trials 
• eConsent

• Patient Reported Outcomes
• Electronic Patient-Reported Outcome Measures: An Implementation Handbook for Clinical Research

• ePro
• eDiary
• eCOA
• AI/ ML
• EHR
• EDC
• PDAs

• CROs 
• Clinical Sites 
• Sponsors
• Data Management
• Statistical Programming 

AI: Artificial Intelligence

API: Application Programming Interface 

BYOD: Bring Your Own Device 

BYOT: Bring Your Own Technology 

CDISC: Clinical Data International Standards Consortium

CRA: Clinical Research Associate 

DCT: Decentralized Clinical Trial

EDC: Electronic Data Capture

eDiary: Electronic Diary

EHR: Electronic Health Records

ePRO: Electronic Patient Recorded Outcomes

EMAs: Ecological Momentary Assessment 

FDA: Food and Drug Administration 

JSON: JavaScrip

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Sam and Ivanna speak Adam Walker about the transformation in clinical data from his experience with CROs, sites and sponsors. Adam takes us through how clinical data collection has evolved from paper forms, to being collected digitally and now fully integrated with patients’ existing devices. This shift increases the volume of data available, the quality of the data, but also puts additional pressure on the industry to make sense of the data in real time. Adam makes the point that technology companies have an advantage in identifying the value of the information collected - not only for treatment, but also to support preemptive lifestyle choices. His advice for anyone working in this field is to “not take the comfy chair” of how we used to do things. 

“The data has not changed, but how we collect it has changed” 

• Adam Walker 

Notes

• Guest Adam Walker: https://www.linkedin.com/in/adam-walker-2327951/ 
• 21st Century Cures Act: https://www.fda.gov/regulatory-information/selected-amendments-fdc-act/21st-century-cures-act  
• The 100 Year Life by Lynda Gratton and Andrew J Scott: https://www.100yearlife.com/ 
• Declaration of Helsinki: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/ 
• ICH: https://www.ich.org/
• GCP: https://www.ema.europa.eu/en/human-regulatory/research-development/compliance/good-clinical-practice
• CPRD: https://www.cprd.com/
• CDISC: https://www.cdisc.org/ 
• Clinical Trials overview: https://www.clinicaltrials.gov/ 
• Huxley Morton Podcast: https://www.huxleymorton.com/podcast.php 

Technology mentioned

• CTMS
• ePro
• eDiary
• RWE/ RWD
• AI/ ML
• EHR
• EDC
• Wearables
• Smartphones 
• Zoom

Functions mentioned

• Statistical Programming 
• Data Management 
• Biometrics

Abbreviations & Definitions

AI: Artificial Intelligence
CDISC: Clinical Data International Standards Consortium
CTMS: Clinical Trial Management System
CPRD: Clinical Practice Research Datalink
EDC: Electronic Data Capture
eDiary: Electronic Diary
EHR: Electronic Health Records
ePRO: Electronic Patient Recorded Outcomes
FDA: Food and Drug Administration 
GCP: Good Clinical Practice
ICH: The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use
MHRA: Medicines and Healthcare Products Regulatory Agency
ML: Machine Learning
NHS: National Health Service
RWD: Real-world Data
RWE: Real-world Evidence

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Sam and Ivanna speak to Angela Slocum about the difficulty in quantifying the benefits of risk based monitoring when mostly you find no issues in your data. Angela does share an example of a fraudulent site being uncovered through risk based monitoring. We speak about how having experience from multiple clinical functions enables a unique platform for innovation when new demands arise but also when implementing software in the clinical space. We also dwell on managing change in our industry, and how conquering fear is vital even when working with highly skilled experts.   

“The science is so much more sophisticated than it used to be. There is much more data than there used to be. The data types and the amount of data are vast. And the roles and skills needed to support all that have evolved” 

• Angela Slocum 
  
  

Notes

Guest Angela Slocum: https://www.linkedin.com/in/angela-slocum-160b48126/ 

Risk-based monitoring (TransCelerate): https://www.transceleratebiopharmainc.com/rbminteractiveguide/what-is-risk-based-monitoring-rbm/introduction/ 

Technology mentioned: 

• SAS 
• JReview 
• Spotfire 
• EDC
• AI/ ML
• elluminate

Functions mentioned: 

• Statistical Programming 
• Data Management 
• Clinical Operations 
• Analytics 
  
  

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