Virtual 17th Annual Meeting of ISMPP

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Day 2 key take-homes and insights

Opening remarks & keynote – writing for equity & inclusion: the role of empathy in medical communications - Georgia Palmer (Project Coordinator, Oxford PharmaGenesis)

Medical communications are reaching a wider audience than ever before, including diverse stakeholders, patient organizations and patients; therefore, inclusivity in writing has never been more important. Stacy Robson (cofounder of CommunicateHealth) took the audience through a presentation explaining the importance of using empathy and inclusivity in our writing to enable the audience to feel heard and seen. Demonstrating empathy to patients has been shown to increase medication adherence and to improve patients’ satisfaction, emotional health and symptoms, so it is vital to continue to do this.

Everyone has unconscious biases and, consequently, all medical communications contributors should make conscious, active decisions to encourage empathy, inclusivity and transparency in their writing.

Top tips

  • Use the correct language.
    • Sex and gender: ‘sex’ is biological; ‘gender’ is social.
    • Male/female: instead of writing ‘X was born male/female’, use wording such as ‘X was assigned male/female identity at birth’.
  • Make a conscious effort to check that pronouns are correct; if unsure, consider using ‘they’ in a singular context or alternating between ‘he’ and ‘she’.
  • Use the right level of specificity regarding identifying factors.
    • If it is not relevant, do not include it, for example, ‘doctor’ instead of ‘female doctor’.
    • However, if it is important to demonstrate results, do include it, for example, ‘patients from lower economic backgrounds experienced …’.
  • Use person-first language, for example, ‘a person with a disability’ instead of ‘a disabled person’.

Ask the experts – the use of technology tools in accelerating scientific evidence dissemination - Elizabeth Coe (Associate Medical Writer, Oxford PharmaGenesis)

Artificial intelligence (AI) is becoming increasingly involved in all stages of drug development. By picking out previously unrecognized patterns from large volumes of text or data, new information can quickly be identified. Identifying novel biomarkers quickly, repurposing existing drugs to target alternative diseases and accelerating personalized treatment were a few benefits mentioned.

Machine learning, a subtype of AI, can be used to optimize clinical trials, a currently costly and unsustainable part of the drug development process. AI can identify the patients who are most suitable for clinical trials to increase the likelihood of successful treatment. Also, utilizing smartphones or wearable devices to set reminders and to record data can improve patient adherence. Improving the likelihood of a successful clinical trial not only saves time and money but also gets new therapies to patients quicker.

Knowledge graphs are another form of AI used in clinical research. They also bring data from multiple databases together into one place to identify previously unknown relationships; however, unlike machine learning, knowledge graphs make it possible to identify the sources used to generate any conclusions.

Finally, the advantages of AI also extend to the medical communications community. AI may be increasingly used as a tool to support literature searches and screening, and data extraction and analysis, as well as topic summarizing and publication of manuscripts.

The future of scientific writing and journal articles – with user-experience (UX) design - Alan Cowland (Medical Writer, Oxford PharmaGenesis)

Scientific journal articles have been developed under the current ‘IMRaD’ format (introduction, methods, results and discussion) since the 17th century; however, this ‘print-based’ format is not optimized for use on the internet. Adopting a user-experience (UX) design could revolutionize the dissemination and understanding of science.

The advent of access to published material through the likes of PubMed and Google Scholar has left scientists drowning in information and crippled by inexact search terms when interrogating unhelpful file formats. The proposal is that articles are fully in HTML format, a continuous text field of permanently updatable text into which machine readability can be coded at key points and for which review is more constructive. Information and data-presentation formats would be tailored to the reality of how people actually view and absorb information from a screen; in short, writing like a human, for humans.

Open-access formats would allow peer review from any expert anywhere in the world, and open comment can counter risks of overclaiming in the interpretation of results. UX design would enable information to be found more quickly and efficiently, and it has the potential to enhance understanding and increase accessibility. Furthermore, exploiting the potential of web-based information would encourage curiosity, enhance diversity and inclusion, and quite possibly speed up progress in science and medicine.

Equity, diversity and inclusion: defining a road map for our profession - George Gomez (Medical Writer, Oxford PharmaGenesis)

The recent global COVID-19 pandemic has shone a spotlight on the importance of diversity and inclusion in clinical trials as well as on the dissemination of information to all sectors of the public. Our profession is motivated to improve global public health communication in line with the diversity in the populations of clients and patients. Truthful and accurate representation of the global community in clinical studies leads to better public health, improved health outcomes for patients and increased public trust in the scientific community.

We are in a position to advocate for diversity in representation in clinical trials; representation of the diversity of the patient population is critical in interpreting clinical trial data that affect patients worldwide. A spectrum of genetic and metabolic diversity exists in different clinical trial subpopulations. Therefore, inclusion of diverse populations in clinical trials helps to involve communities that are typically excluded in studies and enables clinical trial results to be more relevant in different socioeconomic, cultural and global contexts.

The involvement of patients and diverse populations in study steering committees, publication authorship or presentations could be a valuable tool in engaging all members of the public. When people can ‘see themselves’ in clinical trials and scientific presentations, it helps to build trust with patients and encourages them to become more active participants in the healthcare process.

The creation of open access plain language summaries that are broadly understandable by a large proportion of the population likewise facilitates the involvement of diverse populations. The use of inclusive, jargon-free and culturally appropriate language, deliberate pathways that attract and provide access to broad socioeconomic strata, and internet portal and social media outreach to diverse community sectors also facilitates the involvement of diverse populations.

Open access to clinical trial results and scientific literature promotes equity through accessibility because access to published content should not be dependent on socioeconomic status or life circumstances (such as living in a conflict area or a region with limited media access). Giving patients easy access to scientific content enables them to share their experience and expertise with healthcare professionals. The great public demand for information, accompanied by appropriate education and information dissemination, fosters the establishment of a trust relationship between industry and the diverse general public and strengthens the collaboration needed to improve global health outcomes.

Equity and excellence - George Gomez (Medical Writer, Oxford PharmaGenesis)

A diverse workforce promotes the economic success of our industry. Collaboration with individuals who have a mix of talents, skills, experiences and backgrounds fosters innovation by allowing people to think creatively while using diverse approaches to problem-solving.

Recruitment of a diverse mix of candidates can be facilitated by practices such as appropriate wording of job descriptions, training of interview panels, use of blind CVs (to avoid name discrimination) and  creation of support systems prior to onboarding. Since science, technology, engineering and mathematics (STEM) careers are often inaccessible to certain communities, and younger generations of students often have different priorities or value systems, our industry must adapt to these considerations and recruit diverse talent from non-traditional sources.

While a diverse workforce is beneficial for recruitment, workforce retention is a critical aspect of success. Mentorship facilitates retention because it helps to build relationships and creates deep connections between individual stakeholders. Mentorship could begin at any time (such as with university students) and continue throughout a stakeholder’s career. Relationships must be built across differences and generations so that all stakeholders can benefit and thrive as a result.

A diverse workforce engages employees by promoting a supportive work environment. This is aided by soliciting input from current employees on important issues or barriers to personal growth. Encouraging an employee to ‘bring their whole self’ enables them to ‘bring their best self’. This translates into increased economic viability because engaged employees are 43% more productive.

The finance and technology industries have developed best practice for networking with and recruiting a diverse workforce via digital platforms. Organizations of any size can apply the best practice developed in these industries; it is important to make the commitment to implement, and ensure sustainable application of, this best practice.

Artificial intelligence (AI) in drug development - Kim Wager (Communications Consultant - Informatics and Data Science, Oxford PharmaGenesis)

Oxford PharmaGenesis’ own Kim Wager presented a session on artificial intelligence (AI) in drug development.

From the ancient Greek automata to AlphaFold’s incredible accuracy for predicting protein folding, people have always been fascinated with the idea of AI and our ability to build machines that can imitate and surpass the workings of the human mind. In the past decade, this area has progressed immensely, and the uses for AI in drug development are many.

AI can be utilized throughout the pharmaceutical product lifecycle and has the potential to revolutionize the often lengthy and expensive drug development landscape. In terms of early drug development and discovery, AI can help accelerate early R&D and inform portfolio decisions. It can be involved in literature data mining, target predictions, structured-based design and for optimizing screening protocols. Some examples of questions that AI can help address in these early stages include: What are a set of targets for a given disease area? Which compounds might be good for which target?​ Which type of biological pathways could be considered?​ What relationship might a gene have with a set of diseases and drugs?

Beyond drug discovery, AI can help optimize clinical trials and their outcomes. AI methods can be implemented to improve patient–trial matching and recruitment, adherence to trial methodology and endpoint assessment; all common clinical trial pitfalls that can arise during patient selection/recruitment and trial management.

Finally, AI can support and improve many areas of the publication professionals’ work through literature searches and screening, as well as data extraction and analysis.

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