As we kick off 2024, we wanted to start the new year with a series of 2024 Health IT predictions.  We asked the Healthcare IT Today community to submit their predictions and we received a wide ranging set of responses that we grouped into a number of themes.  In fact, we got so many that we had to narrow them down to just the best and most interesting.  Check out our community’s predictions below and be sure to add your own thoughts and/or places you disagree with these predictions in the comments and on social media.

All of this year’s 2024 health IT predictions (updated as they’re shared):

• John and Colin’s 2024 Healthcare IT Predictions
• Health Equity Predictions
• Healthcare Cybersecurity Predictions
• Telehealth and VR Predictions
• Value Based Care Predictions
• Pharma IT and AI Predictions

And now, check out our community’s Pharma IT and AI predictions.

Archana Hegde, Senior Director, Integrated PV Solutions at IQVIA
The evolution of artificial intelligence (AI) such as generative AI has just begun. The excitement around new tools took hold of all industries in 2023, and the potential is expansive. In the coming year, we will see more AI tools begin to be built into existing workflows, rather than acting as a standalone aid. For the pharmacovigilance space, for example, this automation will begin as a tool for recommendations, suggestions or options for potential safety reports, but it will not fully replace human efforts particularly as there are concerns around data output consistency. It is key for pharmaceutical companies to recognize that efficiency does not override compliance, patient safety or regulatory standards.

There is a growing interest in the integration of safety services with technology, and this will continue into 2024. With subject matter experts providing necessary insights to guide technology, companies will see efficiency, cost savings and overall collaboration.

Though organizations will look to conduct this integration quickly, they must first construct roadmaps for this fusion, as an overall “instantaneous” approach will not be sufficient or feasible. The unification of technology, services and pharmacovigilance expertise in the coming year will further enunciate the industry’s focus on patient safety.

Joel Morse, CEO & Co-Founder at Curavit Clinical Research
1) Digital Therapeutic (DTx) companies will continue to pivot away from prescription models. In 2023, Pear Therapeutics filed for bankruptcy and Akili abandoned the prescription business model. Both DTx companies raised hundreds of millions of dollars by going public in SPAC transactions. While each company successfully gained FDA approvals, the current market acceptance for prescription digital therapeutics is low and improvements will take years. Given this, many DTx companies will pivot away from the prescription model and go straight to consumers next year. They will continue to run clinical trials to confirm their claims and value proposition but will not seek FDA approvals.

2.) Health Economics Outcomes Research (HEOR) will become more common in decentralized clinical trials (DCTs). This year we saw the maturation of Claims and Health Information Exchanges, which enable a cost-effective and straightforward process for researchers to gain access to identified patients’ data. Given the improvements in costs, trial sponsors can now take advantage of these exchanges at scale and leverage the data for both pre-screening and health economic analysis. As DCTs and virtual site acceptance accelerates, a knock-on effect will be that more of these trials will include HEOR analysis.

Jane Reed, Director of Life Sciences at Linguamatics, an IQVIA company
Pharmaceutical developers have always prioritized drug safety. Now, they have new tools such as artificial intelligence (AI) and machine learning (ML) that they can leverage to automatically scour medical literature for information to assist signal evaluation and medical review, or real-world-evidence insights that can lead to drug-safety improvements. Drug developers can use these tools to inform routine information-discovery tasks that would require much more time for humans to execute, including benefits-risk evaluation and safety assessments. Combining different types of NLP (deterministic rules-based NLP, transformer models, LLMs for generative text) enables teams to use the right tool for each task, combining automation with human-in-the-loop review for expert validation.

Riccardo Butta, President of the Americas at Stevanato Group
In 2024, we can expect progress around men’s health, specifically in prostate cancer. Today, the five-year survival rate is nearly 100% thanks in part to the development of Monoclonal Antibodies (MABs) which mimic natural antibodies and recognize and attack specific proteins on cancer cells.

The spotlight won’t just be on science; pharma companies will share the stage. Discussions will focus on the nuanced packaging and delivery requirements for MABs, emphasizing the commitment to safety standards while ensuring the drugs’ effectiveness.

AI/Automation in Pharma and Healthcare
In 2024, the pharmaceutical landscape can expect a continued shift as AI continues to reshape drug development and healthcare practices. Across genomics, proteomics, and patient data, AI algorithms are beginning to decipher vast datasets to discover new drug targets, refine clinical trials, and tailor treatments to individual patients. The application of machine learning and deep learning is enhancing the creation of predictive models, cutting costs, and simplifying the timelines of drug development.

AI’s influence also optimized drug manufacturing processes, enhancing efficiency, and reducing waste. The AI revolution has been and will continue to redefine the pharmaceutical industry in 2024, promising transformative outcomes for patients.

Dave Latshaw, CEO at BioPhy
1. Significant Increase in Big Pharma M&A as Biotech Rebounds
Data-Driven M&A Strategies: In 2024, generative AI is expected to significantly aid in sifting through vast datasets to identify optimal M&A targets in the biotech sector, focusing on companies with innovative pipelines and technologies that align with Big Pharma’s strategic goals.

Streamlining Due Diligence with AI: AI technologies will likely be crucial in conducting efficient and thorough due diligence, examining potential M&A targets in the biotech industry for their scientific innovation, financial stability, and market compatibility.

Enhanced R&D Synergy Identification: By analyzing research portfolios and pipelines, generative AI can identify synergies and complementary assets between companies, guiding decisions on mergers and acquisitions to foster innovation and growth in biotech.

2. Bigger Focus on Pharma Supply Chain Resilience Due to Threats Resulting from Geopolitical Issues
Scenario Modeling for Supply Chain Risks: Generative AI can create complex models that simulate various geopolitical scenarios and their impact on the pharma supply chain, aiding in the development of robust contingency plans.

Predictive Analytics for Supply and Demand: The technology will likely be employed to predict supply and demand dynamics affected by geopolitical changes, enabling more agile and responsive supply chain strategies.

Diversification Strategies: Predictive AI can assist in identifying alternative suppliers and logistic routes, helping pharma companies diversify their supply chain to reduce reliance on geopolitically sensitive regions, thus enhancing overall resilience.

3. Streamlining Regulatory Compliance with AI
Automated Compliance Monitoring: In 2024, AI is predicted to automate the monitoring of regulatory compliance in drug development, efficiently tracking changes in global regulatory requirements and ensuring adherence to these evolving standards.

Predictive Analytics for Regulatory Approval: AI’s predictive analytics capabilities could forecast regulatory approval outcomes based on historical data, helping companies to strategize and address potential regulatory hurdles in advance.

Enhanced Documentation and Reporting: AI tools are expected to streamline the documentation and reporting processes in regulatory affairs, using natural language processing to generate and organize required documents more accurately and swiftly.

AI-Enabled Regulatory Intelligence: In 2024, AI is anticipated to enhance regulatory intelligence by continuously scanning and interpreting global regulatory landscapes, aiding pharmaceutical companies in effectively navigating different regulatory environments.

Facilitating Stakeholder Engagement: AI tools might be employed to facilitate better engagement with regulatory stakeholders, by analyzing feedback and guiding pharmaceutical companies in addressing regulatory concerns more effectively and collaboratively.

Updesh Dosanjh, Practice Leader for Pharmacovigilance Technology Solutions at IQVIA
In 2024, the traditional pain points of the pharmacovigilance (PV) space will not disappear. Case volumes will continue to grow while the number of individuals working in the field will not follow suit. The PV model is broken, and in 2024, companies will need to assess how automation can fix operations. While this automation is necessary, there is hesitation to implement technologies and tools such as generative artificial intelligence (AI) and machine learning (ML). Before incorporating advanced automation, organizations must take a holistic look at their processes. Adding automation to an inadequate process will help mitigate issues in the short term but will be detrimental for long-term operations. The PV space is resistant to change, especially because validating new systems can take months. However, organizations need to proactively make a shift, or this change will be forced upon them.

In the upcoming year, we will see the expansion of new, more complex markets and updated requirements from regulators. The balance between monitoring for these adjustments and maintaining the growing volume of cases will be tenuous. Without fixing the current, broken PV models, the continuous cycle of more complexity in the market, which then pushes organizations to incorporate automation into insufficient processes, will massively hinder PV operations. This will become more evident in the upcoming year, and organizations will be forced to reimagine their models.

Pouria Sanae, CEO at ixlayer
In 2024 we can expect care teams to get bigger, broader, and more collaborative as new digital tools and care strategies combine to shift the status quo. Convenience, cost, and consumerism remain top-of-mind going into the New Year, and more healthcare stakeholders are considering offering at-home tests to close gaps in care and advance better health.

For example, pharma companies are now starting to engage in at-home diagnostic testing initiatives, including telehealth consults to review results – a task traditionally assigned to primary care and specialists. The trend is driven by a growing focus on health equity and proactive, personalized care. Sending tests to patients’ homes helps overcome SDOH barriers that may prevent patients from getting to a lab for testing. This will lead to more comprehensive screenings, which in turn will result in earlier diagnosis and treatment of chronic disease. For pharma companies, that means a significant number of patients who could benefit from currently available therapies may soon be getting the treatments they need to stay healthy.

Michelle Gyzen, Senior Director, Regulatory Affairs and Drug Development Solutio at IQVIA
The desire for rapid adoption of intelligent automation technology will be widespread in 2024. While tools like artificial intelligence (AI) show a lot of promise for the pharmaceutical regulatory industry, many are not quite ready for all the challenges that will follow. There are considerable risks to adoption that may have deep compliance implications. Human efforts are the greatest asset in the journey to automation in terms of compliance and validation, and organizations will see this firsthand in the upcoming year.

As new systems and automated technologies are built, global health authorities will need to respond accordingly. In the next few years, we will see greater collaboration and consolidation with how health authorities will accept submissions. There will be a big push for component content management, and possibly the reinvention of the electronic common technical document (eCTD). Though it may not happen in 2024, the industry will take some strides to eventually see end-to-end automation for eCTD submissions. The most exciting aspect is the potential of the combination of AI, machine learning and large language models to help decipher and manage health authority communications. By leveraging an organization’s intelligence and existing information, organizations will be able to efficiently respond to health authority queries with the assistance of AI.

The regulatory industry is typically hesitant to embrace innovative technologies. However, in the past year, there was a new understanding and appreciation for what can be achieved and optimized. This will push organizations to look towards the phased implementation of automated tools for the regulatory field. In the same vein, we expect organizations to take a more thoughtful approach, really taking time for change management, retraining and repurposing staff as automation enhances their work.

Jason Rose, CEO at Adhere Health
2024 will spark transformational change across the pharmaceutical industry. CVS’s proposed drug pricing formula is likely to compel other major retail pharmacies to move to more transparent, lower-cost pricing models. While this shift may ultimately lead to lower costs for consumers, it could also create additional problems for certain rural and urban areas with “pharmacy deserts” as independent pharmacies may not have the scale and efficiency to compete.

This pharmacy desert challenge is an important social determinant of health (SDOH) barrier that leads to reduced health equity for vulnerable, higher-risk consumers. Independent pharmacies have struggled for years to stay afloat as they deal with issues such as DIR (direct and indirect remuneration) fees. It is important to ensure our most vulnerable people are getting the proper care and health equity.

Simon Johns, Director, Medical Information and Marketed Product Safety at IQVIA
The continuously growing volume of Medical Information case inquiries will not cease in 2024, especially as it is effectively the only inbound communication channel remaining for pharmaceutical companies. Artificial intelligence (AI) will be relied on to help manage the growing case volume. Although AI is not a novel concept within the pharmaceutical industry, the introduction of new systems and tools – like generative AI – will push companies to revisit their current applications to automate traditionally manual tasks.

In 2024, the industry, specifically within the Medical Information area, will see shifts to multi or even omni channel models to ensure that healthcare professionals and patients have available means of communication with pharmaceutical companies when necessary. AI chatbots will first be applied to this area in the form of warm transfers – if a call center is experiencing a surge in calls and all human agents are occupied, AI agents will emerge as a backup. These chatbots would then be able to transfer the inquiry to a human agent when available or needed. Fully automated processes will be phased in. Against some beliefs that this process will replace agents, AI will be a tool for agent assistance and faster response.

Maintaining compliance is a priority for pharmaceutical organizations, and while the gradual integration of AI processes may seem like a large endeavor, organizations will begin to see the benefits in the upcoming year.

Ian Chan, CEO and Co-founder at Abpro
The global supply chain issues and continued difficulties securing funding amid economic uncertainty caused challenges for many life sciences companies this year. In 2024, I believe we’ll see an uptick in innovation across the industry, especially as AI capabilities continue to progress and become more and more ingrained in a myriad of applications – from expedited drug development to accurately identifying diseases. I anticipate that smaller biotech companies will consider multiple avenues for securing funding, including through SPAC deals similar to the one that we at Abpro announced this year. The top priority for biotech in 2024 will be getting potentially life-altering therapeutics into the hands of the patients who need them more quickly and efficiently.

Dr. Kate Sasser, Chief Scientific Officer at Tempus
AI is accelerating drug development and fueling enrollment in clinical trials: AI-enabled diagnostics and AI-empowered clinical trials will expand and start to drive greater impact in the clinic and in drug development. As drug development gets more precise, finding very specific patient profiles for clinical trials or therapy, becomes much harder. With larger, interconnected data sets in the healthcare systems, AI will be able to identify those needle-in-a-haystack patients, and match them to the appropriate clinical trials or therapies.

Manu Garg, Vice President, Head of Healthcare Consulting at Definitive Healthcare
AI adoption will be crucial for biopharma and medical device companies in 2024. While 42% of life science leaders state lack of skilled talent as a roadblock to AI adoption in their institutions, we will see more life science leaders collaborating with large tech companies to build and pilot programs that meet organizational needs. Collaborating with experts from tech companies will empower life science businesses to embrace the technology and negate major fears around security, quality and ethics of AI implementation.

Michel Denarie, Senior Principal, RADDS at IQVIA
In the coming year, clinical trial sponsors will become even more focused on implementing diversity plans and this will continue to push for major shifts across the industry. In fact, within the United States, guidance has been introduced for the creation of diversity plans in clinical trials to push further diversity and inclusion. This is a critical step for drug development as patients must be representative of the population, but it is key to note that it must be done cautiously to be compliant with the expectations of health authorities.

Project optimizations from the FDA, specifically Project Optimus within oncology, is a recent trend that will expand to other therapeutic areas in the coming year. Rather than testing only the maximum efficacy, organizations have been pushed to find the therapeutically optimal drug dose. This dose optimization could soon be a de facto requirement, elongating the trial process and increasing overall costs – beyond oncology.

In terms of indication prioritization, organizations will begin to integrate natural language processing and artificial intelligence for optimization and efficiency. This automation will help reduce the manual time spent on data analysis, allowing senior team members to focus more on operations that require a high level of human expertise. This integration will happen slowly, but steady, as automated technologies must be validated for accuracy.

Angie Franks, Chief Executive Officer at Kalderos
There will be continued conversations in 2024 around whether patients are benefiting from drug discount programs, such as 340B and MDRP (Medicaid Drug Rebate Program). And the future of technology in this space will get a lot of attention. We need to explore ways to simplify what has become a complex system to enable greater efficiency and drive down costs. Finally, drug discount stakeholders need to stop being so adversarial and start working together by leveraging tech to streamline processes, enable data sharing, and increase transparency, all of which are critical to building trust. Let’s all focus on how the rebate programs can benefit patients who need drugs at affordable prices. The fighting has to stop if we want to improve healthcare. Fortunately, I think the willingness is there.

Be sure to check out all of Healthcare IT Today’s Pharma IT and AI content and all of our other 2024 healthcare IT predictions.