To truly step up its game and embrace its changing remit, those in medical affairs roles need to address a number of challenges.
Improving patient experiences and outcomes requires the constant handling of a wide range of data sources, the clear articulation of product value over time, as well as engaging with HCPs and patients more directly.
Medical Affairs need as much support as possible to carry out these activities efficiently and effectively on an ongoing basis. Adequate resources, as well as tailored tools and new technologies, are pivotal to the success of medical affairs teams, especially given the high stakes of drug development and commercialization.
Five areas where Medical Affairs professionals can deploy digital tools to optimise processes and produce faster, more relevant results:
A clear handle on the breadth and depth of existing research is invaluable to update internal knowledge, identify gaps in research attention, and pinpoint areas where there is scope for innovation – among the many benefits.
Equipped with tools that build research overviews, medical affairs can support and direct research and development (R&D) investment into areas where it may provide a more significant impact on overall development outcomes. This is especially critical given that the average drug development cost is more than $2 billion. Fewer than 10% of drugs in development make it to market from phase I clinical trials, and despite the acceleration of research efforts (Figure 5) and of digital transformation, return on investment for R&D at large biotechnology firms has consistently declined for the last decade.
A better early understanding of the research landscape, as well as efficient sharing of relevant insights across the organisation, can save businesses significant money and time. However, gaining a clear overview of the full scope of research in each field and sub-field is not straightforward and rests on the analysis of multiple inputs from a growing number of sources.
Figure 5: Total global spending on pharmaceutical research and development from 2014 to 2028 (in billion U.S. dollars)
When making strategic research decisions, it is important to understand the current research landscape – but running multiple complex searches and analysing streams of data can be daunting.
Dimensions is the largest scientific research database and connects the dots across publications, grants, clinical trials, policy docs and patents – creating billions of connections across the research lifecycle.
This landscape analysis dashboard includes easy to use filters and visualisations to understand, at a glance, the research landscape of any given topic.
The Landscape & Discovery app allows users to horizon scan in seconds quickly filling knowledge gaps.
You can:
Figure 6: Keyword co-occurrence diagram for ‘pain’, generated in a Dimensions landscape analysis dashboard.
The more datasets are available, the more they are studied; in other words, the rising tide of data availability is creating more opportunity for analysis, further expanding the volume of clinical studies.
While this rise in high-quality clinical research is beneficial for the industry, it has become increasingly challenging to search through these volumes under pressured time scales to respond to queries – whether internal or from external players such as HCPs and insurers – and make a robust case for pharmaceutical products.
Improving patient outcomes remains the key objective for medical affairs and its achievement goes hand in hand with promoting safe and appropriate use of medication. Ease of use for patients and physicians, since it impacts comfort, safety and patient outcomes, also remains key. However, the increasing availability of data means that medical affairs professionals have to sift through this data with speed and efficiency so that the right information (and the right drug) is provided at the right time to patients and providers.
Once patients are diagnosed with prostate cancer, for instance, clinicians need to choose from a wide variety of available drugs and make an informed decision on the right drug combination for each patient.
Pfizer partnered with Dimensions to help support clinicians working with sufferers of prostate cancer.
To expedite the decision-making process, Dimensions developed a prostate cancer agent combinations dashboard.
This is an open access tool that collates relevant publications in relation to all identifiable prostate cancer drug combinations. Clinicians can then base their prescriptions on all the relevant data available.
This data is constantly updated, powered by the Dimensions database. Thanks to this vast repository of data, a similar approach can be applied for any therapeutic area and any research topic, to create a unique dashboard.
The interactive dashboard allows healthcare professionals to filter results in a given area to focus on what is relevant to them and their patients. They can also use gap analysis to identify both established treatment combinations as well as areas where little or no research exists, informing their courses of treatment (Figure 7).
The greater the sharing of research data, the greater the impact on patient care and positive outcomes in the fight against disease.
Figure 7: Extract from Pfizer and Dimensions’ interactive dashboard. The dashboard brings together medical literature and clinical trials investigating therapeutic sequencing and combinations of agents in prostate cancer.
“We cannot afford not to know what is already known”.
Growing volumes of observational and clinical outcome data are being gathered digitally by national health systems but also by independent organisations such as UK Biobank, a large-scale biomedical database, which has gathered genetic and health information from half a million UK participants since 2006.
Apart from clinical papers, other potentially relevant unstructured data may be in the form of clinical papers, notes from patient visits or even social media interactions. Thoroughly mining this mass of material is almost impossible without using artificial intelligence and machine learning tools. Leveraging these tools could support multiple elements of the ever-expanding and increasingly important medical affairs function.
The existence and availability of this data effectively puts the medical industry under pressure to use it, and to do so effectively to transform patient outcomes. As one commentator explains, “there is a moral obligation to maximise its potential to improve healthcare”.
There is limitless potential to improve patient outcomes by harnessing the vast data available; this in turn can only help to build trust in the industry as a whole. However, healthcare data is spread across disparate sources. One way of managing this is through data pools. Strong partnerships can connect different data sources and pool everything from claims to electronic medical records (EMRs), providing medical affairs teams internationally with access to wide-ranging data sets in a more organized way. Selecting evidence that is fit for purpose from all these external sources also requires the assistance of machine learning tools and advanced analytics.
In a changing world, new communication channels are continuously emerging. Patients and HCPs use these channels to share experiences and information and therefore they have been integrated into the sources that regulators accept or even demand. For example, in the next three to five years, reports anticipate increased Food and Drug Administration (FDA) interest in RWE and acceptance of this data, as well as increased openness to novel trial designs and endpoints.
As a result, it is even more important that medical affairs professionals identify suitable tools to help them monitor and analyse new and sometimes unstructured data sources, so that they can easily extract relevant data.
Clinical trials typically take place in the later stages of the drug discovery process, meaning that a failure at this stage involves losing the entire trial investment. The main causes for failure are usually suboptimal patient cohort selection and recruiting techniques before clinical trials and the inability to monitor patients effectively during the trials.
Both these errors can be significantly curbed by leveraging the deep and nuanced understanding of customers that medical affairs professionals develop over time. Supporting Medical Affairs and MSLs can optimise patient recruitment for clinical trials increasing efficiency and probability of success.
Since AI can be used to organize diverse datasets, such as electronic health records (EHRs), medical literature, ‘omics’ data and trial databases – which may be in many locations and saved in different formats – it becomes possible to build patient profiles for trials in a more informed manner. As data volumes are growing, the data available is also becoming more granular, and so, patient selection processes can be increasingly focused and streamlined through AI. Over time, machine learning can identify patterns in patient features that can then be used to select patient phenotypes most likely to benefit from a proposed drug or intervention.
Additionally, AI-powered patient-matching algorithms leads to more diverse trial cohorts; one study estimated that, in 2014, 86% of clinical-trial participants worldwide were of white ethnicity. Supplemental environmental, economic and social data can also be integrated if they may influence therapy response and study success. This could include, for instance, air pollution or the educational level of patients.
In future, vast data sets may be used to simulate how cohorts are likely to respond to a therapy, so that pharmaceutical companies can avoid initiating real-world trials that will fail. Technology companies such as Apple and Google are becoming more active in the clinical area, further broadening and expanding the streams of data available.
The experience of the recent pandemic has shown us that building effective partnerships can significantly speed up innovation so long as the selection process is based on relevance and experience.
In addition to this, it is also key to ensure that partnerships support existing products but also help bridge gaps where further R&D is required.
Finding suitable KOLs is the cornerstone of partnership building, but medical affairs professionals need to make their way through a crowded research space to identify both established academics and organisations as well as potential rising stars in their clinical area. Having a clear understanding of the specific disease communities means moving beyond simply relying upon known experts to identify new profiles that will stimulate future discussions.
This is a complex evaluation that needs to take into account: the experience of the KOL; how vocal they are; whether they are active on social media; what speaking engagements they have had, how many, and how authoritative; and how frequent their publications are and how often these are referenced.
Fortunately, there are digital tools that enable the aggregation of KOL behaviour into a single profile, making it easier to condense, compare and profile KOL activity.
Discovering the right KOL is essential for a drug’s success. But how do you speed up this search and discover not just the KOL's of today, but those of the future too?
Using the combined power of Dimensions and Altmetric data, we are now able to identify up-and-coming key opinion leaders – otherwise known as KOLs – and digital opinion leaders (DOLs), by looking at the most recent data and trends.
The work we have been doing has centered around reconciling traditional data and metrics with online community spaces.
Our Dimensions dashboard can already surface KOLs in academia, but two years ago we started to match all Twitter users with Dimensions authors and now we have a six-figure number list of academics who tweet. This ability to spot rising stars offers significant strategic value in medical affairs, as KOLs can be recruited based on emerging data to provide a medical affairs team with a competitive advantage.
“The data is very accurate and clean. What it means is that we can, at scale, report on what happens with academics on social media… “If academics on Twitter can say something about a topic they have authority, and authority has impact. It’s very exciting.”