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IMPALA Podcast Series – Subscribe via Spotify so you never miss an episode!

Sharon Havenhand and Jeremy Jones are the hosts of this new IMPALA Podcast Series, where they invite guest speakers to join them in discussing key topics  from the IMPALA space and share the impact it is having across the biopharmaceutical industry.

Check out the episodes below:

Episode 1: What is IMPALA?

• In this episode Sharon and Jeremy are joined by Timothe Menard, Co-Founder of IMPALA and Mike Pelosi, Co-Chair of IMPALA’s Strategic Steering Committee and Co-Lead of the Education Work Product Team. Listen as we discuss what IMPALA is and what they are trying to achieve.

• You’ll also get the chance to hear more about the current IMPALA work products, Tim and Mike’s vision for the future of IMPALA before they wrap up with how you can get involved!

Episode 2: The Data Driven Quality Professional

• In this episode Sharon and Jeremy are joined by Mike Pelosi, Co-Chair of IMPALA’s Strategic Steering Committee and Co-Lead of the Education Work Product Team, Joanna North, Co-Lead of the Education Work Product Team and Roshan D’Souza, Member of the Education Work Product Team.
• Listen as they delve into the industry-leading initiatives of the IMPALA Education Work Product Team and learn about what’s key to becoming a Data-Driven Quality Professional in the dynamic world of biopharma.

Episode 3: Introduction to Data Basics

• In this episode Sharon and Jeremy are joined by Mike Pelosi, Co-Chair of IMPALA’s Strategic Steering Committee and Roshan D’Souza, Chair of IMPALA and Member of the Education Work Product Team.
• Listen as they take it back to the basics and answer fundamental questions such as:
  What exactly do we mean by Data?
  How are we using Data we are generating?
  Has data replaced Oil as the most valuable resource in the world?

They also discuss the emerging world of Generative AI and its application in the BioPharma Industry.
Don’t miss out on these valuable insights, tune in now!

Episode 4: Life of a Data Scientist

• In this episode, Sharon and Jeremy are joined by Pekka Tiikkainen, Lead of IMPALA’s Work Product Package on Anomaly Detection in Clinical Data, as well as Data Scientists Björn Koneswarakantha and Frederik Collin.
• Together, they discuss their individual journeys into the field of Data Science and provide insights into how this area has evolved over time. Furthermore, we will delve into the future of Data Science, exploring the possibilities and potential it holds.
• Lastly, the conversation will focus on the topic of Identifying Anomalies in Clinical Trial Data with CTAS (Clinical Trial Anomaly Spotter). This innovative, free open-source package aims to streamline audits and inspections by prioritizing critical data anomalies and promotes compliance with regulators by providing a systematic approach to data monitoring. Tune in to find out more!

Episode 5: Generative AI in Healthcare

• In this episode, Sharon and Jeremy are joined by Ryan Dugan, Associate Director, Analytics & Insights, MRL QA at Merck.
• Join us as we explore the world of Artificial Intelligence (AI) and its fascinating subset, Generative AI. We begin by clarifying what AI is and then delve into the distinctions between AI and Generative AI.
• We also discuss the sudden surge of interest and advancements in Generative AI over the past year, attributing it to its promising applications in healthcare and touch upon the ethical considerations that come with using this technology.
• We then shift our focus to the impact of Generative AI on the Pharma QA space where Ryan shares some examples of its applications at Merck. Tune in to gain a deeper understanding of Generative AI and its implications in the Healthcare Industry!

Episode 6: Enhancing Clinical Trial Integrity with Data Driven Audit Site Selection

• In this episode, Jeremy is joined by new members of the IMPALA Consortium: Meera Nagaria, Senior Data Scientist at J&J; Lucie Régné Martos, Clinical Quality Performance & Risk Management Head at Sanofi; Cedric Liu, Associate Director, AI/ML at Biogen; CJ Jassal, Head of Quality and Governance at Biogen; and Deepak Bandyopadhyay, Data Science Group Leader at J&J.
• Tune in and listen as they discuss the shift towards data-driven clinical audit site selection, the challenges in implementing these strategies, innovations in current practices, and how the IMPALA Consortium is advancing data-driven methodologies in clinical trial site selection.

Transforming Trial Audits: A Deep Dive Into Data-Driven Clinical Site Audit Selection in Pharmaceuticals

Published in RQA QUASAR #169, November 2024 – Transforming Trial Audits: A Deep Dive Into Data-Driven Clinical Site Audit Selection in Pharmaceuticals. The paper was led by the Audit Site Selection Work Product Team, which includes authors Hangyu Liu, Elina Beletski, Michael Pelosi, Ofure Obazee, Bjorn Koneswarakantha, and Lucie Regne-Martos. The Work Product Team consists of 10+ IMPALA biopharmaceutical Member Organizations, each providing input on the evolution in data-driven clinical site audit selection in the pharmaceutical industry. This white paper delves into the transformative shift from traditional data-driven methods to more advanced strategies, exemplified by the challenges of automating clinical site audit selection and giving insights into the current practices of the IMPALA consortium member companies. It highlights the need for continuous innovation and industry collaboration to fully realize the potential of data-driven methodologies in enhancing the quality and integrity of clinical trials. In the article, IMPALA Members share a vision for a data-driven clinical site audit selection, led by innovative and efficient processes that revolutionize the quality assurance approach in clinical trials, to be safer, more compliant, and more successful.

Framework for Data Analytics for Quality Assurance in Pharmaceutical Development

The “Data Analytics for Quality Assurance in Pharmaceutical Development Framework” is a collaborative whitepaper which offers insights and guidance on transforming Quality Assurance (QA) in Good Clinical Practice (GCP) and Good Pharmacovigilance Practice (GVP) through the application of advanced analytics.
This Framework reflects on the learnings and key decisions taken by the Intercompany Quality Analytics (IMPALA) Consortium to elevate the goal of advancing analytics in GCP and GVP. This framework can guide Quality Assurance in development, implementation and enhancement of their analytics and technology strategy, regardless of organizational maturity.

Submit your information to view the Framework here.

Work Product Team Lead: Michael Pelosi

Open-source Package for Clinical Safety reporting

The IMPALA Clinical Safety Reporting Work Product Team has developed an open-source R (statistical analysis software) package called {simaerep} that calculates the probability of under-reporting of adverse events for all clinical trial sites in a given study using only patient-level AE and visits data. {simaerep} is available publicly on github (https://openpharma.github.io/simaerep/). It follows general good practices and standards for R packages, has a high unit test coverage which is tested by an automated pipeline which creates a validation report that is attached to the latest release.

Read more about the package here. 

Work Product Team Leads: Ronojit Adyanthaya and Björn Koneswarakantha

Open-source Clinical Trial Anomaly Spotter (CTAS) Package

The Clinical Trial Anomaly Spotter (CTAS) is a powerful tool for Central Statistical Monitoring that identifies outliers and anomalies efficiently and accurately in clinical trial time series. Its main focus is on flagging sites with one or more study parameters whose profiles differ from those of the other sites. In addition, the results can be used to identify anomalies for individual subjects.

Development of the package was spearheaded by Pekka Tiikkainen, Principal Clinical Data Scientist at Bayer, and tested and adapted for user flexibility across organizations by members of IMPALA’s Anomaly Detection in Clinical Data Work Product Team. The underlying algorithm of the CTAS operates by defining one or more time series for each parameter. The algorithm summarizes time series into a set of features such as Mean, Standard deviation, Unique value count, and Autocorrelation. These features help in identifying individual subjects with suspicious data.

CTAS represents a significant advancement in clinical trial data analysis; however, IMPALA’s vision for CTAS extends beyond its current capabilities and usage. CTAS has the potential to be an industry-standard tool that can significantly enhance the integrity and reliability of clinical trial data, leading to more accurate research outcomes and ultimately, better patient care.

IMPALA proudly invites all interested partners to test, utilize, and provide feedback for this innovative package.

Work Product Team Lead: Pekka Tiikkainen

Case study – Leveraging analytics for remote clinical quality oversight

This case study, presented at the 2nd APEC – Asia-Pacific Economic Cooperation Roundtable Dialogue, discusses opportunities for Post-Pandemic Regulatory Innovation Convergence, such as how analytics can help detect and mitigate issues faster, reduce the burden of retrospective, time-consuming traditional QA activities and ultimately accelerate approval and patient access to innovative drugs. View the full presentation here.

RQA Workshop on Data Analytics

The goal of the RQA Workshop Work Product Team was to engage with Industry and Inspectors in an open dialog on how Data Analytics can be used to speed up Drug Development. The workshop took place at the RQA Conference in Brighton in November 2022, and resulted in lively discussion and wide-ranging ideas.

View the summary, write-up, and video here.

Work Product Team Leads: Joanne Donald and Timothe Menard

DIA Global 2023

The DIA Global Meeting held in Boston from June 25-29, 2023, brought together professionals from the pharmaceutical industry, regulatory agencies, and research organisations. IMPALA was grateful to have a great delegation of members and to have three sessions to showcase some of the work products the Consortium is focusing on. It also afforded the group a chance to connect in person for collaborative exchange and conversation. Click for details on the different sessions where IMPALA was represented.