Call for Papers – Drug Safety

Call for Papers – Drug Safety

Drug Safety invites the submission of original research articles (up to 6000 words) on the Role of Artificial Intelligence/Machine Learning in Pharmacovigilance for a themed issue of the journal to be published in 2021. The issue is guest edited by Dr. Andrew Bate (GSK) and Dr. Yuan Luo (Northwestern University). With a mix of invited review articles and original research articles, the theme issue will provide a comprehensive coverage of how emerging technologies can affect work tasks and further improve the field of pharmacovigilance.

We welcome proposals for original research articles on the following topics:

  • Methods for identifying safety signals in any or combinations of data source

Author Brief: The article will showcase novel research on how pharmacovigilance can benefit from the continuously increasing number and form of data sources, especially electronic health record data and patient self-tracked/self-collected data. In addition, the article will discuss how machine learning has helped improve identifying safety signals from these data sources for pharmacovigilance.

  • Prediction, in future numbers of adverse events or types of safety outcomes, or change in severity in RCT, PSPs, RWD or other data sources e.g. prospective surveys

Author Brief: The article will showcase novel machine learning methods for predicting outcomes such as future numbers of adverse events or types of safety events, or change in severity in randomized controlled trials (RCTs), patient support programs (PSPs), real world data (RWD) or other data sources e.g. prospective surveys. Of particular interests is how the methods will account for longitudinality and missing data from the above data sources for pharmacovigilance prediction.

  •  Visual pattern recognition in safety

Author Brief: This article will describe the novel application of visual pattern recognition to support signal detection in pharmacovigilance.

  • Developing test sets for assessing machine learning algorithmic performance

Author Brief: The article will showcase efforts for developing test datasets for assessing machine learning performance in pharmacovigilance tasks such as predicting future numbers of adverse events or types of safety events. The article will need to demonstrate rigorous annotation process e.g., inter-annotator agreement evaluation and quality control. Of particular interests is the actual release of a  dataset for pharmacovigilance prediction.

  • Developing frameworks for increasing transparency or explainability of machine learning outputs (including visualization) as well as assessing how to best implement into routine use

Author Brief: The article will showcase efforts for developing novel methods to assess and ideally increase the transparency of machine learning models in predicting pharmacovigilance outcomes either at systemic cohort level or at individual patient level. Adoption and/or implementation of such efforts in real world pharmacovigilance is a plus. Integration of multiple data sources to collate on each other and improve transparency is also a plus. Of particular interests is the open-source release of such a system.

  • Methods work in building capabilities to facilitate case processing and intake

Author Brief: Both regulators and pharmaceutical companies have very complex processes with many steps to get reports into their databases. The article will focus on robotic process automation and machine learning-based approaches to make report entry more efficient and effective.

  • Approaches for assessing quality, reliability, credibility and trust in machine learning outputs

Author Brief: The article will showcase efforts for evaluating quality and reproducibility of machine learning models in predicting pharmacovigilance outcomes either at systemic cohort level or at individual patient level. Evaluation on a large multi-institute dataset is ideal. Detailed error analysis on generalizability and reproducibility is a plus. Of particular interests is the open-source release of such a system to establish some “industrial standard”.

Please submit an abstract describing your proposed paper by 30 April 2021 to nitin.joshi@springer.com. Full papers will be invited by 30 May 2021 and manuscripts due by 31 August 2020.

Drug Safety is the official journal of the International Society of Pharmacovigilance (ISoP) and is indexed in all major databases. It is published by Springer Nature under the Adis imprint.

The World Drug Safety Congress in Amsterdam addresses key challenges

The World Drug Safety Congress in Amsterdam addresses key challenges

Adis Pharmacovigilance attended the World Drug Safety Congress in Amsterdam on Sept 10th and 11th.

The event has been running for over a decade and is world renowned for its ability to connect key stakeholders in the drug safety field, as well as for leading the way in moving the sector forward.

Senior level drug safety professionals, as well as representatives from sponsors and service providers, met to discuss key topics and showcase solutions.

This year’s theme, Addressing Key Challenges for Safety Professionals, had us prepared for a series of interesting presentations and discussions on the ever growing importance of pharmacovigilance and the challenges connected with ensuring patient safety. Continue reading “The World Drug Safety Congress in Amsterdam addresses key challenges”

FDA to revisit guidelines for biosimilar development pathway

FDA to revisit guidelines for biosimilar development pathway

In September 2017, the US FDA made public a draft industry guideline entitled “Statistical Approaches to Evaluate Analytical Similarity.”[1]  Its aim was to provide advice, to sponsors developing biosimilar agents, on how to demonstrate that the product under investigation is “highly similar” to the referenced biological. After taking into consideration the public comments relating to the document, the FDA withdrew the guideline in June 2018 for further evaluation and development to ensure that the scientific and regulatory issues that had been raised would be appropriately addressed.[2] Continue reading “FDA to revisit guidelines for biosimilar development pathway”

1998 Shirov: Bishop to h3! Dubbed an all-time strategic chess move… How do future pharmacovigilance strategies compare?

1998 Shirov: Bishop to h3! Dubbed an all-time strategic chess move… How do future pharmacovigilance strategies compare?

Report: Pharmacovigilance Strategy Meeting, Boston, MA, USA November 2017

In less time than it took for me to travel to the meeting from New Zealand – the day was over! Hard to believe that within a short eight hours, 25 lively roundtables were conducted, two keynote speeches were delivered, and the panel discussed the learning of the day, including challenges of monitoring diverse sources, importance of real-world evidence in the context of risk benefit, and the game-changing impact of artificial intelligence. Continue reading “1998 Shirov: Bishop to h3! Dubbed an all-time strategic chess move… How do future pharmacovigilance strategies compare?”

Fail Early, Fail Fast – and increase Likelihood of approval with biomarkers

Fail Early, Fail Fast – and increase Likelihood of approval with biomarkers

Our partners Amplion recently published an interesting blog post on the benefits of biomarkers in informing earlier decisions in the drug development process – “fail early, fail fast” to save time and money, and increase approval success. An interesting read, check it out! Continue reading “Fail Early, Fail Fast – and increase Likelihood of approval with biomarkers”

Meeting report: 3rd Annual Risk Management and Pharmacovigilance Summit, Vienna

Meeting report: 3rd Annual Risk Management and Pharmacovigilance Summit, Vienna

Colleagues from SpringerNature recently took part in the 3rd Annual Risk Management and Pharmacovigilance summit in Vienna, with the following meeting report provided by Daniela Ranzani, Adis Business Intelligence Product Manager.

Traditional topics as well as best practice and case-study presentations remain at the core of the meeting, allowing attendees to share knowledge and diverse experiences. Regulation revisions were also discussed, with a spotlight on the GVP Modules V and IX updates. Attention to patients with dedicated programs was highlighted, and a presentation on social media listening reminded us all of the great power represented by such tools when used for PV, which also brings great challenges in terms of carefully managing this type of information. Continue reading “Meeting report: 3rd Annual Risk Management and Pharmacovigilance Summit, Vienna”