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Revolutionizing Pharma Patient Assistance Programs, KnippeRx Leads the Future of Patient Care

It’s no secret that the pharmaceutical industry is facing a myriad of challenges and disruption, such as complex, costly, and lengthy new drug development; global regulatory hurdles; more start-ups entering the market every day, increasing competition; new technology and data solutions; lingering supply chain disruption, and more. Pharma leaders need to think differently about how to run their businesses—and bring their people along with inevitable transformative change. As leaders look toward the future, the companies that will outpace and outperform their competitors will be those that can embrace and scale adaptability and agility in their operations.

In addition to a continued focus on growing drug pipelines, and the increasing use of artificial intelligence (AI) and data in research and development (R&D), pharmaceutical companies have a renewed focus on the supply chain. In 2024, major companies like Reckitt, AstraZeneca, and Novartis scoped out plans to expand their manufacturing footprint, and it’s likely that many others will follow suit in 2025. In a recent survey, 90% of pharma executives said they are investing in smart manufacturing to increase supply chain efficiency.

A common thread in all the top priorities is a high degree of uncertainty and a need to build flexible approaches to capture value and weather unpredictable market conditions. Having management strategies and systems that have adaptability at the core will be critical to success.

What we know about adaptable organizations

The highest performing organizations are, and will continue to be, those that create and nurture adaptability in a variety of ways. At the heart of it, this requires creating more leadership from more people—up, down, and across the business. There are three critical characteristics that adaptable organizations possess.

Change-friendly systems, structures, and processes

Adaptable organizations are those that have management systems in place that are open to and able to change, while being able to respond to emerging factors in the market, technology, and internal demands. They can establish formal systems and processes that balance efficiency and agility. For example, rather than adopting rigid three- to five-year strategic plans, they embrace principles-based decision making and ground their plans in assumptions about the future that are revisited frequently. They focus on outcomes over process. They target talent strategies with an emphasis on what will be needed for the future, rather than what worked in the past. When the formal management systems in place are more change-friendly, organizations can be more proactive in responding to new opportunities in the market, such as the use of AI to accelerate new drug development and smart devices along the manufacturing line.

Organizational culture emerges from the behaviors and norms that are reinforced over time. A focus on culture is not a “nice to have” and it is not about “employee perks” or “employee satisfaction.” The highest performing companies establish and nurture adaptable cultures, those that allow them to appropriately respond to both threats and opportunities. The core characteristics of these cultures include: taking a multi-stakeholder view (employees, shareholders, customers, vendors, and the community), embracing appropriate risk-taking, balancing both a short- and long-term view, and biasing towards proactivity even without perfect information.

Broad-based knowledge and skills for leading change

Often, talent development strategies focus on deepening technical skills. While these are important, they are not enough on their own, especially since the required technical skills are changing rapidly. Companies need to invest in helping their people build stronger change muscles, developing both the knowledge and the skills to apply that knowledge to their jobs. Skills such as the ability to articulate a compelling vision of the future, manage challenges to new ideas and ways of working, inspire and mobilize others even without direct authority, and implement strategies to overcome barriers to change are key to developing a workforce that creates a competitive advantage.

Each of the characteristics outlined above can be cultivated through deliberate action. There are a set of key strategies that will help address change friendly systems, adaptable culture, and broad-based knowledge and skills.

The first step toward addressing the disruptive factors facing the pharmaceutical industry is for senior leaders to get hyper-clear on the opportunities ahead, why you are positioned to seize those opportunities, and why you must act now. For example, it is undeniable that AI has the potential to dramatically accelerate new drug development by assessing large and disconnected data sets, analyzing relationships between these data sets, and prompting new hypotheses to be tested.

 It can also be utilized to anticipate the effectiveness of various drugs, assess side effects, identify target populations, and explore alternative uses for drugs already on the market. But how AI is implemented, and what benefits it will unlock, need to be tailored to each organization—where it is today, the capabilities already in place, and where the business is looking to go in the future. Shaping this narrative around the opportunities it can unlock, rather than being reactive and focusing on the challenges it presents, is critical.

It's not enough to be aligned in theory; leaders need to be actively engaged in making the opportunity a reality. They need to communicate way more than leaders typically assume is necessary. Deliver the message in multiple forums, through multiple modalities, and continue to beat the drum. Then, find ways to demonstrate meaningful action, and remove barriers that could get in the way of others taking action. And, recognize that this “action” may actually mean stopping efforts that are not aligned or contributing to the desired future state.

When leaders are aligned and truly activated, you will enable much faster, and bolder, decision making.

Responding to disruptive factors in the industry cannot stop at the executive level. Keeping up with the pace of change requires contribution from people at all levels and across all functions. Find opportunities for employees to not just execute ideas that come from the top, but rather, create space for them to identify opportunities, surface ideas, and then experiment with implementing these new ideas. When employees are empowered and engaged in this way, you can create a sense of passionate buy-in and ownership.

A global vaccine company did this exceptionally well. After facing numerous warning letters from the FDA, they recognized the need to shift their culture, imbuing a sense of ownership across the business around a “quality mindset.” Senior leaders articulated their opportunity, acknowledging that this mindset would allow them to save more lives, and then unleashed the power of the workforce to make it a reality. Employees from the manufacturing lines to R&D to corporate shared functions all came together to create a movement, enabling the surfacing of a host of ideas. Shop floor workers co-developed training, new standards around QDCI boards, and more, leading to zero operator errors at their site. Others experimented with new ways to label samples, retube machines, and engage their peers—all leading to significant reductions in defects, thousands of work hours saved, and more than 5,000 people actively engaged in the effort. At the end of the transformation, the FDA deemed the transformation one of the most successful turnarounds they had ever witnessed.

While many employees will get onboard with new ways of working, especially if the opportunity is framed in a compelling and inspirational way, there will always be skeptics. To build momentum, demonstrate progress and ensure efforts are driving meaningful results (not just “feel good” activities). It is imperative to not only track wins along the way but to intentionally engineer them. Start with the end in mind and then work backwards to determine critical milestones, leading indicators, and desired behaviors that will enable the ultimate goal. Once these are identified, use the power of the workforce to make these proof points a reality, and make a point of spotlighting them when they happen. Not only will this create a wave of momentum that helps bring skeptics along, but it will also help develop an unrelenting focus on value.

Navigating the choppy waters and disruption facing the pharma industry will require organizations to foster more adaptability. To keep up with customer demands, emerging technology, and shifting regulatory changes, pharmaceutical leaders need to evolve how work gets done. Investing time in aligning and activating leaders and then engaging the workforce to drive new ways of working and meaningful results is critical to unlock and maintain a competitive advantage. In today’s world, adaptable organizations are going to be leaps and bounds ahead.

Gaurav Gupta is managing director and head of R&D, while Vanessa Akhtar is managing director and head of consulting, both at Kotter.

1. Breakthroughs or bottlenecks? Pharma industry outlook, trends and strategies for 2025. 

https://www.zs.com/insights/pharmaceutical-trends-2025-outlook-ai-supplychain-and-beyond#:~:text=Pharma%20companies%20are%20investing%20heavily,AI%20in%20R%26D%20for%202025

2. Artificial intelligence is taking over drug development. 

https://www.economist.com/technology-quarterly/2024/03/27/artificial-intelligence-is-taking-over-drug-development

Why having these strategies for results—amid disruptions—will be critical to success. 

Building Adaptability in the Pharmaceutical Industry

James D. Chambers, PhD, MPharm, MSc, is a health economist by trade. After earning his MSc in Health Economics from the University of York and his doctorate in that same focus with Brunel University’s Health Economic Research Group, he has gone on to pursue various endeavors along that track, most recently as a professor of medicine at the Tufts Medical Center Institute for Clinical Research and Health Policy Studies and a health economist spokesperson for Organon.

 to uncover the latest regarding biosimilars—biologic medical products that are considering highly similar to their reference products—to lay out how in fact they can lead to cost reductions, while boosting patient access; their economic impact; challenges to implementation and recommendations for faster implementation; and emerging trends in the sector.

Could you elaborate on how biosimilars have the potential to reduce healthcare costs and increase patient access to treatments? What are the key factors driving these outcomes?

Biosimilars have the potential to reduce healthcare costs and increase patient access to essential treatments by offering more affordable alternatives to expensive biologics. Since 2014, biologics have made up 37% of net drug spending, totaling $120 billion,

 highlighting the need for cost-effective options. Globally, biosimilars have demonstrated success, particularly in Europe, where they provide 20% of treatment volume and drive savings from reduced list and net prices of the referenced medicines. In the US, biosimilars are projected to save the healthcare system $38.4 billion from 2021 to 2025,

 and have already provided more than 344 million additional days of therapy, expanding treatment access.

You mentioned that there are economic dimensions of biosimilars that are often less explored. Could you share some of the crucial economic factors that should be considered when assessing the full impact of biosimilars on the healthcare system?

Biosimilars introduce significant economic value, particularly by increasing competition in the biologic drug market. This competition drives down prices, undercutting reference product prices, thereby potentially reducing overall treatment costs and expanding patient access. By providing lower-cost alternatives to reference biologics, biosimilars also push reference biologic manufacturers to adjust their pricing strategies.

As biosimilars gain more market share, they reshape payer and provider decisions, leading to improved formulary coverage and promoting more cost-effective treatment options. This shifting market landscape underscores the potential of biosimilars to generate both direct savings and broader economic benefits, ultimately enhancing affordability and accessibility across the healthcare system.

Despite the potential benefits, biosimilars face barriers to adoption. What are the most significant challenges preventing their widespread use, and how can these be addressed at both the policy and market levels?

A major barrier to the adoption of biosimilars in the US is the variation in coverage policies across commercial health plans. My team’s 2019 study, using the Tufts Medical Center Specialty Drug Evidence and Coverage (SPEC) Database—which includes specialty-drug coverage decisions from 17 of the largest US commercial health plans that make their decisions publicly available (covering 60% of commercially covered lives)—found that plans covered biosimilars as “preferred” in only 14% of decisions.

 More recently, a 2023 study revealed that 19.4% of biosimilar coverage decisions were more restrictive than those for their reference products.

 These restrictions are often due to rebate walls, where reference biologic manufacturers offer significant rebates to payers, making it harder for biosimilars to compete for formulary inclusion.

Another major barrier is the lack of education and familiarity with biosimilars among healthcare providers. Many physicians remain hesitant to prescribe biosimilars despite strong evidence supporting their safety and efficacy. Addressing these challenges requires stronger educational initiatives targeting both healthcare professionals and patients. Additionally, greater alignment of policies across stakeholders—such as payers, PBMs, and providers—will help reduce coverage inconsistencies and foster broader biosimilar adoption.

In your work with the Specialty Drug Evidence and Coverage (SPEC) Database, have you identified any emerging trends or patterns that suggest biosimilars will become a more integral part of healthcare in the near future?

In 2024, using the Specialty Drug Evidence and Coverage (SPEC) database, my team analyzed coverage, market share, and pricing data for seven originator products and 20 corresponding biosimilars. The analysis found that preferred coverage of multiple products increased from 30% to 76% between August 2017 and August 2022, signaling growing acceptance by health plans.

This shift indicates the increasing role of biosimilars in healthcare as healthcare plans recognize their potential for cost savings and expanding patient access. The market dynamics around biosimilars are also evolving. For instance, biosimilars with list-price savings (relative to reference products) of $15,000 or more per patient per year were less likely to be restricted in coverage, demonstrating that cost-effectiveness influences payer decision-making. Furthermore, the introduction of biosimilars in therapeutic areas like oncology and rheumatology is intensifying competition in markets traditionally dominated by high-cost biologics. As these trends continue, we anticipate that biosimilars will become more widely integrated into treatment regimens.

From a health economics perspective, what strategies or interventions would you recommend in order to incentivize faster adoption of biosimilars, particularly in markets where they are still struggling to gain traction?

To accelerate biosimilar adoption, a multifaceted strategy incorporating policy adjustments, education, and market dynamics is essential. A key intervention is adjusting coverage policies to better align with cost savings.

Although research indicates that biosimilars offering significant list-price reductions face fewer coverage restrictions, health plans may impose stricter policies in high-prevalence disease areas where they have negotiated favorable pricing for reference products. Reducing coverage restrictions on biosimilars with the highest cost savings could improve accessibility and drive wider adoption, particularly for conditions with high treatment costs.

Education for healthcare providers and patients is also crucial. It’s key to raise awareness of data and real-world evidence (where it exists) of biosimilars to address and correct potential misconceptions and build confidence in their use. This is why I am collaborating with Organon, a company with a commitment to biosimilars, to share insights and contribute to broader industry conversations, as fostering collaboration among key stakeholders, including payers, providers, policymakers, and industry leaders is crucial for creating a unified approach.

1. Yu T, Jin S, Li C, Chambers JD, Hlávka JP. Factors Associated with Biosimilar Exclusions and Step Therapy Restrictions Among US Commercial Health Plans. 

. Epub 2023 Apr 1. PMID: 37004706; PMCID: PMC10287773.

2. Mulcahy A, Buttorff C, Finegold K, El-Kilani Z, Oliver JF, Murphy S, Jessup A. Projected US savings from biosimilars, 2021-2025. 

3. Chambers JD, Lai RC, Margaretos NM, Panzer AD, Cohen JT, Neumann PJ. Coverage for Biosimilars vs Reference Products Among US Commercial Health Plans. 

 Factors Associated with Biosimilar Exclusions and Step Therapy Restrictions Among US Commercial Health Plans. 

https://doi.org/10.1007/s40259-023-00593-7

James D. Chambers, PhD, MPharm, MSc, professor of medicine at the Tufts Medical Center Institute for Clinical Research and Health Policy Studies, dives into why biosimilars contribute to a reduction in cost and increase in patient access, while highlighting challenges to adoption. 

The Biosimilars Landscape Through the Eyes of an Economist

Over the past few years, the self-injectable pharmaceuticals market has soared to new heights, leaving pharmaceutical companies struggling to meet demand and keep up with changing industry dynamics. According to Research and Markets,

 the global self-injection devices market is expected to reach $67.29 billion by 2035, with a compound annual growth rate of 10.33% during the forecast period of 2025-2035.

With a rise in the adoption of biologics, growing demand for home healthcare options, and an increase in conditions such as diabetes and autoimmune disorders, self-injectables are here to stay, and brands are challenged with implementing manufacturing operations that will keep them ahead of the curve.

The rise in self-injectables has brought a certain set of challenges for pharmaceutical companies to overcome. With meeting patient demand more urgent than ever, combined with supply chain disruptions that can arise promptly, companies are faced with meeting high demand while maintaining quality and regulatory standards. Additionally, the complexity of self-injectables requires manufacturers to seek new production methods and machines that create, fill, and package these devices, shaking up existing processes and flow companies are accustomed to.

However, with challenges come strong opportunities for success. Let’s explore some of the key benefits for pharmaceutical and drug manufacturers to consider when expanding into the self-injectable market.

Historically, most patients have received drug injections from a doctor or pharmacy professional, but more recently, pharmaceutical companies have had the opportunity to interact directly with consumers. With the rise of medications like GLP-1s, consumers are showing increasing comfort with self-injectables, opening the door for consumers to bypass traditional channels and more efficiently secure the medications they need. By showing consumers the safety, ease of use, and convenience of self-injectable medications, pharmaceutical manufacturers are connecting with users directly and empowering them to take control of their health from the comfort of their own homes.

By communicating directly with consumers, pharmaceutical companies must consider the elements needed to ensure that users have all the information they need to correctly and comfortably administer self-injectable drugs. From the primary and secondary packaging to the materials and instructions included inside a package, companies must keep consumer-friendly packaging top of mind when broaching direct-to-consumer operations. Self-injectables and other medical device developments allow for exploration of new technology for dosing, and even medication tracking, adding to the complexity of production. Having a manufacturing line that can encompass the filling, packaging, and collation of products is a key element to streamlining operations, especially as drugs become more niche, and production runs become smaller and more focused.

Due to a rise in diseases and breakthroughs in treatments, pharmaceuticals have become increasingly tailored and complex, leading to the manufacturing of less volume in certain production runs. With an increasing variety of medications that pharma companies offer, there is also a need for increased flexibility in manufacturing operations.

By incorporating filling machines that able to easily switch from one application to another, pharmaceutical companies can boost efficiency, reduce production downtime, increase capacity, and better meet the needs of customers demanding a greater variety of products.

Flexibility of operations also comes with the specs of filling machines that are integral to pharmaceutical manufacturing. With demand for the injectable format on the rise, companies are challenged with adding lines and shifting facility layouts to accommodate appropriate machines. These machines often take up precious facility space, causing ripple effects in changes needed to be implemented for redesign.

Two of the most important components of pharmaceutical manufacturing are patient safety and quality assurance. As drugs become more complex and regulations become more stringent, companies must constantly find ways to ensure the safety and quality of their products.

Through collaboration with original equipment manufacturers (OEMs), pharmaceutical companies can incorporate modules into their equipment—such as electronic components and sensors—to provide checkpoints and visual inspections, reject stations, and processes to pinpoint the source of potential errors. This will allow any product issues to be flagged before they make their way into the hands of patients.

Data management plays a critical role in the prioritization of patient safety. By tracking products down to the component, capturing data throughout the manufacturing process, and monitoring equipment health, pharmaceutical companies can ensure systems are running smoothly and the highest quality products will be distributed to patients safely. Today, OEMs offer a range of digital solutions that can be linked to a customer’s manufacturing execution system software in order to enhance machine monitoring, data analytics, and predictive analysis to increase overall equipment effectiveness, while delivering more efficient and reliable production performance.

If the rise of self-injectable drugs has taught pharmaceutical companies only one lesson, it is that trends ebb and flow, and no one can perfectly predict where the industry will be even a few years in the future. Decades ago, pharmaceutical companies likely could have never imagined patients wanting to handle medication injections themselves. The total shift in sentiment to present-day demand emphasizes the crucial need for future-proofing machines and manufacturing processes.

Drugs of all kinds are getting smarter, resulting in growth opportunities for all types of pharmaceuticals, blending the line between pharmaceutical drugs and medical devices. The industry is evolving, and the success of drugs in new formats is paving the way for innovation across the board.

To keep up with this changing landscape, pharmaceutical companies must consider machines with flexible formats that can consistently be updated. Otherwise, they run the risk of becoming obsolete and facing a need for substantial investment in new equipment.

By having an open mind and aiming to stay ahead of the curve of changing industry dynamics, pharmaceutical manufacturers are poised to weather the challenges associated with a rise in the self-injectable format. With a willingness to stay in touch with consumer needs and finding the right OEM partner to support flexible operations, quality assurance, and futureproofing, companies can open the door to new possibilities for self-injectable drugs and beyond.

Stephen Robinson is a sales engineer with Coesia North America.

1. Self-Injection Devices Market by Product, by Usability, by Application, by Distribution Channel, and by Region. Research and Markets. December 2024. 

https://www.researchandmarkets.com/reports/6032673/self-injection-devices-market-product?utm_source=GNE&utm_medium=PressRelease&utm_code=8jmbpg&utm_campaign=2026100+-+Self-injection+Devices+Market+Forecast+to+Generate+Revenues+of+%2467.3+Billion+by+2035%3a+Analysis+by+Product%2c+Usability%2c+Application%2c+Distribution+Channel%2c+and+Region&utm_exec=jocamspi

As the adoption of biologics rises, demand for home healthcare grows, and conditions like diabetes and autoimmune disorders become more prevalent, self-injectables are here to stay.

How the Rise in Self-Injectables Is Impacting Pharmaceutical Manufacturing

For a child with autism spectrum disorder (ASD), effective care coordination across the required medical, physical rehabilitation, counseling, occupational, and speech providers is challenging, especially when the aim is to provide individualized care—at scale across many patients.

Genial Care, a healthcare company focusing on personalized interventions for children with ASD, provides a successful example of how generative artificial intelligence (GenAI) can solve this problem. GenAI monitors sessions with children and their families, synthesizes session records, improves the records’ quality, tracks each child’s progress, and shares this information with providers and the child’s family via an app-based interface. Plus, the company reduced the manual transcription time from approximately two hours per day to three minutes per session, allowing care providers more time to dedicate to their patients.

However, this is one of only a few examples of a life sciences or healthcare company breaking out of GenAI pilot purgatory. How did they do it? They focused on a practical, human-centered use case that easily integrated into daily workflows and could be efficiently scaled.

Why is the life sciences industry stuck in GenAI “pilotitis"? Several reasons come to mind:

Regulatory constraints around patient data

Risk aversion, stemming from a smaller margin of error related to life-altering decisions, which can be exacerbated by mistrust due to AI hallucinations and viewing AI as a “black box”

Lack of an enterprise-wide AI strategy and organizational readiness, often resulting in siloed efforts, wasted resources, and declining innovation efforts

Limited input from stakeholders, resulting in solutions that don’t solve real problems or fit into existing workflows

Choice of complex use cases with long implementation times and limited impact, resulting in slowed momentum

The light bulb moment: GenAI's potential to illuminate healthcare

The incandescent light bulb’s journey to widespread adoption perfectly illustrates the hockey stick-shaped trajectory of transformative technologies like GenAI. Initial development, which spanned decades from 1835 to Edison's commercialization in 1880, was followed by decades of infrastructure development (power plants, transmission lines) necessary for widespread use. This gradual ascent reflects the “entropy effect”—the disruption to established norms that slows adoption.

Similarly, AI's transformative potential in life sciences, while offering increased speed and accuracy in tasks like synthesizing unstructured data, continues to face resistance, leaving it in the slow ascent phase. To accelerate AI adoption, we can learn from other sectors already leveraging AI at scale.

From auto racing to healthcare: The transformative power of GenAI

Like healthcare, other industries suffer from an overwhelming amount of data. For example, in the world of automotive racing, although a race lasts hours, fans often want a quick summary of the highlights and outcomes. In this setting, a GenAI application was developed to produce a two-minute summary podcast in any language from two hours of race commentary.

 LLM enrichment using driver data and future race events further set the system up for the next race.

In healthcare, this same approach could be used to:

Summarize patients’ entire health histories

Synthesize healthcare professional (HCP) feedback

Suggest next best steps for HCP engagement

Predict future health outcomes and treatment-related behaviors

Streamline benefit verification by payers

We also often want to find specific information from within messy notes or audio or video files. Globant’s Advance Video Search does just that.

 It uses information from a text- or image-based search to prompt GenAI to search vast amounts of video. It can find specific clips, images, and frames within the video files.

Imagine if that same precise search functionality could be used to find:

Personalized, compliant content from a company’s website or patient support site based on a patient’s natural language search terms

Specific patient insights from unstructured clinical notes

For example, we’ve implemented conversational AI solutions in production for multiple life sciences clients where they are able to find insights and answers from large libraries of analyses and notes. Tasks that previously took many hours of painstaking manual research can now happen in minutes. Subtle, yet valuable insights that may have been overlooked before are being brought to the surface.

The Genial Care example mentioned above demonstrates that we are also seeing examples of scalable GenAI use emerging in life sciences. It could also be applied to more than ASD, such as complex rare diseases or patients with comorbid chronic diseases who require care from many different providers.

In addition, Predictive Oncology’s PEDAL platform harnesses AI to make predictions about drug responses in oncology.

 Combining AI, data about drug responses, and a biobank of >150,000 tumor samples from 137 tumor types, the platform uses machine learning algorithms to make predictions about the effect of different drugs on tumors, with an accuracy of 92%. Although the company is using these for drug discovery and repurposing, this type of functionality has implications for clinical care, where the right drug could be identified for the right patient, at the right time.

Another example from a Beghou client involved predictive analytics leveraging 20+ variables into five easily discernable attributes to help drive field alerts. The alerts and suggestions were highly relevant, with the field team taking action on over 75% of them, much higher than industry benchmarks. One alert identified a rural HCP with a potential rare disease patient, which caused their team to prioritize that HCP and ultimately lead to a new patient start.

The AI-generated “digital brain” from Orby is changing neurorehabilitation and pain management for patients who have lost their motor skills due to spinal injury, stroke, or other conditions.

 By mapping neurostimulation to affected brain areas, the company’s able to tap into specific disordered functions. Applications for mental health issues come to mind, where targeted treatment could be delivered.

Within this realm of exciting possibilities, some limitations of GenAI also need to be acknowledged, or what it is not:

These misconceptions feed into the entropy effect, mistrust, and reluctance for adoption. They also highlight the important roles of humans to ensure relevant, accurate, and trusted results, by guiding its outputs; providing oversight to mitigate bias in the data inputs; reviewing the results for accuracy; and giving feedback to improve machine learning processes.

What does this look like in practice? Recommendations could include the following:

Identify unmet needs with the organizational readiness to solve them:

 Find issues that are not currently being optimally met by existing systems and processes where the transition to AI would make a meaningful impact to end users (e.g., commentary summaries, synthesis of unstructured notes, or live audio).

Prioritize low-complexity, high-impact use cases with a focus on scalability:

 Review your high-impact use cases for the level of complexity to implement. Tasks that already have proven AI solutions (i.e., are low complexity), such as tagging and summarizing unstructured data to better understand customer sentiment, result in quick wins that maintain momentum.

 Establish a powerful, compliant infrastructure of data, technology, and governance to ensure long-term scalability.

Center people in the development and implementation: 

Field an end user panel to provide input and feedback throughout design, development, and review, and leverage your team’s expertise to drive context, accuracy, and judgment.

Conduct pilot testing for early exposure and ongoing refinement:

 Allow users to provide feedback during the build to generate excitement, foster trust, and lay the foundation for enterprise-wide adoption and expansion.

Incorporate change management processes: 

Make sure your entire organization is aligned and on board regarding the uses and benefits being pursued with AI, so that, when you go live, your organization speaks with a unified voice and makes a splash.

We believe that stalled or failed GenAI pilots can become a thing of the past in life sciences. Although data-related factors such as volume, structure, and compliance have proven to be problematic for extracting valuable insights and personalizing care, we’ve found that they can be effectively addressed using a human-centered approach and enterprise-wide strategies that drive scalable AI solutions.

Dan Schulman and Vishal Singal are both partners at Beghou Consulting.

1. Google and Formula E Break World Record for Most Participants in Generative AI Hackathon. 

https://www.fiaformulae.com/en/news/504402

2. Globant Releases Innovative Advanced Video Search Tool Leveraging Google Cloud’s Gemini Models. 

https://www.globant.com/news/globant-releases-advanced-video-search-tool-avs

https://predictive-oncology.com/poc-report-page/

By embracing practical, human-centered use cases, life sciences companies are breaking free from GenAI “pilotitis” and demonstrating how scalable AI solutions can help transform patient care and provider efficiency.

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