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Articles

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.

Innovation with GenAI: Lessons from Life Sciences and Beyond

Despite challenges surrounding communication overload, drug shortages, and cybersecurity risks, this term is revolutionizing medication management and patient care through the use artificial intelligence and predictive forecasting. 

The Digital Transformation Reshaping Hospitals and Medication Management

 interview, Claire Riches, vice president of clinical solutions at Citeline, dives into:

Specific inefficiencies in the current drug approval system that are the biggest obstacles to faster approvals

How the FDA can integrate data sources such as real-world data (RWD) to streamline approvals, while maintaining rigorous safety standards

Advancements in data collection and validation that make RWD a viable tool for drug approvals

The role payers and insurers should play in this shift toward a more data-driven, flexible approval framework, and how this could impact patient access to innovative treatments

The likelihood of bipartisan support for reforms that modernize drug approvals with shifting political priorities under HHS Secretary Robert F. Kennedy Jr.

Claire Riches highlights inefficiencies in the current drug approval process, while outlining the role of payers and insurers in shifting toward data-driven approval framework. 

Fast-Tracking the Future

In order to succeed in today’s outcomes-driven healthcare landscape, pharmaceutical companies must move from traditional sales models to strategic, measurable partnerships with integrated delivery networks (IDNs).

Bridging the Gap Between Strategy and Practice in IDN Partnerships

Addressing drug shortages requires the industry to embrace innovative advanced manufacturing processes underpinned by real-time data.

Keeping Drug Supplies Available Means Pharmaceutical Organizations Must Move in Real-Time 

A qualitative study aimed to strengthen systematic repurposing efforts within rare disease nonprofit organizations, while also providing a framework for data-driven drug repurposing.

Themes Among Rare Disease Repurposing Efforts

Ways to reimagine pharma’s operating model and KPIs for commercial success in an AI-driven future.

Measuring What Matters

A multi-national study reveals over half of older adults in several European countries are prescribed five or more medications—spotlighting the urgent need for better data-driven prescribing strategies.

Addressing Polypharmacy Challenges in Europe with Real World Evidence

Decreasing Clinical Development Timelines

Deloitte’s life sciences R&D strategy leader

 describes how his company’s 15th annual Deloitte report on the return on investment (ROI) in pharmaceutical R&D reveals a continued upward trend, with a projected ROI of 5.9% for 2024. This marks a notable reversal from the consistent decline seen throughout much of the 2010s. During that period, ROI dropped largely due to a more challenging commercial environment, which reduced the projected value of drug pipelines. This was influenced by both business dynamics and a shift toward developing treatments for more specific, nuanced patient populations, often with smaller market sizes.

However, the past two years have shown a positive turnaround, with year-over-year increases in projected ROI. Two key drivers are behind this recent momentum. First, the overall projected value of late-stage drug pipelines has grown, especially when adjusted for risk, signaling stronger confidence in the commercial viability and clinical success of these therapies.

Second, a small number of exceptionally high-value drug programs have had an outsized impact. Among these, treatments in the GLP-1/obesity space stand out, significantly boosting the total value of the late-stage pipeline. These high-potential programs are reshaping expectations and driving much of the improvement in projected R&D returns.

The renewed optimism in pharma R&D ROI is largely attributed to an increase in risk-adjusted value across the pipeline and the emergence of breakthrough therapies in lucrative areas such as obesity treatment, highlighting a shift toward more valuable and promising innovation.

Dondarski also comments on the strategies companies can adopt to manage or mitigate escalating drug development costs; current best practices for balancing long-term pipeline sustainability with short-term financial returns; how GLP-1’s success influence future investment strategies in high unmet-need areas; how AI and automation realistically reduce clinical development timelines; and much more.

How can AI and automation realistically reduce clinical development timelines, and what barriers are currently limiting their widespread adoption in R&D?

If I think about what the barriers or limitations are, I think there's two that come to mind. The first is the decision of, do we want to be first, or do we want to [focus on] the velocity that companies are taking to adopt it? There're some companies who've decided to immediately jump in the pool and go all in. Then, there's other organizations that are kind of waiting to see how the technology matures before they make that hurrah.

The second piece is the fragmentation of decision autonomy, and how those technologies can benefit different parts of the organization. There’s so much utility in a lot of the things that we see in deployment—it crosses functional boundaries. Even if there's the recognition to move forward with something, you need alignment from multiple functions within R& D. Within R&D IT, there's usually security or cyber concerns, so it's really just an alignment exercise.

I feel like that's a major barrier that, on one hand, seems simplistic compared to what the R&D part of the industry is actually doing, but it can't be understated. I think that's been a barrier for different organizations.

I think we're at an interesting inflection point. To your first question, when GenAI really became a thing or became more of a part of the public vernacular, there was a lot of emphasis on POCs and MVPs and individual use cases, etc. I think there's a lot of success associated with that. I think what we see now is a broader migration to stop thinking about, let's say, individual point-in-time or point-in-the-value-chain applications, and more of how can this enable a more transformative way for us to think about the end-to-end value chain.

The easiest examples that come to mind are within content generation or document authoring, where the same capabilities have utility across all aspects of the lifecycle, and I think we're really starting to see a push in that direction. I think there's still some uncertainty with respect to the more innovative or research side of the equation, where I think there's an appreciation that leveraging data and AI can accelerate different processes and ways of driving innovation, but more is to come in that world, or it's still too early to tell, in terms of how disruptive it can be in research.

In the third part of his Pharma Commerce video interview, Kevin Dondarski, Deloitte’s life sciences R&D strategy leader, dives into the barriers limiting AI and automation’s widespread adoption in R&D. 

How to Manage Rising Drug Development Costs

Despite the rising ROI, the cost of developing a drug has climbed to $2.23 billion. What strategies can companies adopt to manage or mitigate these escalating costs?

I think about it in two parts. The first is, what's actually driving the cost and the cost increase over time? I would say, generally speaking, that there's probably three factors that are really responsible for that. First and foremost is always attrition. Failure is always an issue. The later stage the failure, the more of an impact that it has specifically, because the figure you mentioned is more or less a normalized amount for what companies are spending to get an approval.

The second is R&D inflation. Certainly, if you follow the news, inflation has been a factor over the last couple of years. I think that within the world of R&D and R&D services, costs have risen even more so. Third, and finally, I think it oftentimes is the competitive dynamics, specifically in the clinical world. With so much of the industry focusing on similar areas, you don't normally use the word “competition” for patients, but the reality is, there're so many studies that end up taking longer to recruit, and that drives costs off. If I think about that, every company has probably a different area that they focus on if they're trying to address the cost part of the equation.

There’s so much of an effort at all the different companies where we serve to try and think about how in two areas. One is, how can you just really double down on operational efficiency? Much of that is through data and AI, which is perhaps the least surprising thing ever. Then the second is continuing to ensure that what companies are focusing on within their pipeline, A) they feel like they have a differentiated way to kind of pursue either that molecule or that indication, given their knowledge of the disease area, and then B) ensuring that there's the appropriate degree of rigor and discipline when it comes time to making either go, no-go, or investment decisions to ensure that you’re really maximizing the utility of how you deploy your R&D capital.

In the second part of his Pharma Commerce video interview, Kevin Dondarski, Deloitte’s life sciences R&D strategy leader, outlines strategies that companies can adopt to help mitigate these increasing costs.

A Change in Healthcare Education and Provider Awareness

, Colin Banas, MD, DrFirst’s chief medical officer, describes have many Americans face significant challenges in accessing GLP-1 drugs due to their high cost. Despite the growing popularity and usage of these medications, which were originally developed for diabetes treatment, the price remains largely unchanged. Even with insurance coverage, patients often encounter co-pays or out-of-pocket expenses upwards of $500 to $600, making the medications unaffordable for many. Research indicates that once out-of-pocket costs exceed $100, medication adherence drops dramatically, further limiting access.

Additionally, insurance companies frequently require patients to try other medications first, a process known as step therapy, which can delay access to GLP-1 drugs. The drugs' weight loss benefits have garnered attention, but insurance companies still primarily cover them for diabetes treatment, leaving individuals seeking them for weight loss without coverage options. Moreover, as ongoing research uncovers more potential benefits of GLP-1 drugs—such as their positive effects on cardiovascular disease, Alzheimer's, and chronic kidney disease—insurance policies have not yet adapted to these expanded uses. As a result, many Americans who could benefit from these drugs for conditions beyond diabetes find that coverage is not available.

Banas also comments on patients turning to direct-to consumer (DTC) platforms following insurance denials; rumors of DTC advertising being banned; and much more.

What are your thoughts on the rumors that RFK Jr. could potentially ban DTC advertising?

As a provider it might be mixed, but there's actually an interesting consequence of DTC ads, and it is conversation and it is education, meaning, as a provider, I am also exposed to what my patients are being exposed to. I see the advertisement at the Super Bowl, or the flyer in the magazine or the web page. A lot of these therapies, a lot of these drug classes, are brand new and accelerating so quickly that it is actually very hard to keep up.

In a roundabout way, if I see that, and if I'm bombarded with it as a provider, I actually take that as a cue to, ‘oh, I need to educate myself,’ not necessarily on that drug in particular, but on that therapy class. The reason is, ‘wow, there's something new that's out there. I should be on top of it,’ and, ‘oh, I think I'm going to get questions about this.’ I do think that's an interesting side effect of DTC.

The other thing I'll say about RFK—there are a lot of things on pause right now. There's a lot of trepidation, especially in the health IT world. What is going to happen with existing road maps, around interoperability, around some of the CMS initiatives that providers are participating in? I will say it does seem to be a tech-forward administration, and so I do think there's going to be advances—maybe even accelerations—in artificial intelligence, hopefully in interoperability, and the digitization of the medical record. Because a lot of these things can't be accomplished without data, and you can't get the data unless you're collecting it, aggregating it, and using it in an appropriate way.

In the final part of his video interview with Pharma Commerce Editor Nicholas Saraceno, Colin Banas, MD, DrFirst’s chief medical officer, shares his thoughts on the rumors that RFK Jr. could potentially ban DTC advertising.

Overcoming Health Data Blockages in Polypharmacy

, Tom Dorsett, CEO, RazorMetrics, describes how polypharmacy refers to the use of five or more medications by an individual, and it is becoming an increasingly prominent issue in the United States. Polypharmacy has been recognized for years but is growing more significant, especially within Medicaid, Medicare, and large commercial sectors, including self-funded employers.

One of the key drivers of this rise is the growing number of chronic conditions, which affect a large portion of the adult population. Around 40% of adults in the US have four or more chronic diseases, contributing to the increase in polypharmacy. Furthermore, among the working adult population between 40 and 79 years old, 24% are impacted by polypharmacy, a trend that continues to grow. This issue highlights the complexity and challenges of managing multiple health conditions and medications in an aging population, leading to potential risks related to drug interactions and overall healthcare management.

Dorsett also explains why he believes this concept is such an overlooked driver of unnecessary spending and adverse health outcomes, strategies that should be taken to overcome health information exchange blockages, and much more.

What strategies should be taken in order to overcome the health information exchange blockages that are associated with polypharmacy and its cascade of side effects?

 What the US healthcare system lacks at this point is ample health information exchange. We did a really good job back with the HITECH [Health Information Technology for Economic and Clinical Health] Act back in 2008, where $22 billion was put out there for the mass adoption of electronic health records. By and large, the whole system is electronic at this point, but those systems still experience data blocking. The 21

 Century Cures Act has gone a long way in trying to remove those blocks between health organizations—they don't necessarily like to share that information because it makes it a lot easier for the patient to go over to another health system if their data is readily available.

The other issue is that EHR vendors themselves don't necessarily like to play ball in that regard. What this creates is a situation where you've got these EHRs not talking to each other. If I go see my cardiologist at one system and am prescribed a statin for my high cholesterol, and for whatever reason, maybe I get referred because I'm on a health plan where you have to have a referral, I get referred over to another system. I might go in, and if I'm not really highly aware of the particulars of the medication, and I don't mention that I'm already on it, they're not going to have any visibility to that at this other institution, and they may prescribe me another statin. This happens all the time.

My co-founder, Dr. Siva Mohan, is a semi-practicing Interventional Cardiologist at Emory, and he sees this almost every day. He practices at Emory, and then patients go over to Piedmont and get prescribed another statin. You have that duplication, which can be very dangerous, and it's due to the fact that they aren't communicating. It’s not their fault—it's just that the systems aren't built to do that in most cases. That's one of the areas where we're able to help, because we see a holistic view through the claims of all the medications, but the duplication issue is a big problem too with polypharmacy.

I think if that can get ironed out at some point, it's been a huge challenge, and maybe they're able to fix it through some sort of government-run utility. I think that's probably what it'll take. They tried to do it by doling out a bunch of money at the same time they were doing the EHR subsidies for physicians and institutions, but by and large, any sort of organization that was trying to exchange information could go purchase their own application or network to do this, and even those wouldn't talk to each other. It largely failed, sadly, and it's really gone a long way towards creating this issue.

In the third part of his video interview with Pharma Commerce Editor Nicholas Saraceno, Tom Dorsett, CEO, RazorMetrics, shares the strategies that should be taken to overcome health information exchange blockages.

AI's Role in Shaping the Future of Pharmaceutical Development

chair of the FDA Regulatory practice at Lowenstein Sandler, discusses the potential impact of upcoming tariffs on pharmaceutical supply chains, focusing on Canada, Mexico, and China. He believes that tariffs on Mexico and Canada would have minimal effects on supply chains, as the pharmaceutical industry sources relatively little from these countries. The real concern lies with China, which is a major supplier of active pharmaceutical ingredients (APIs) and finished drug products. A significant portion of recent pharmaceutical deals has involved licensing Chinese drugs, which could be affected by tariffs if they disrupt supply chains.

If the relationship between the United States and China worsens, tariffs could have a more substantial impact. Specifically, they might increase the cost of generic drugs, since China is a crucial supplier for these products. Despite this, Shehan notes that many generic drugs are already extremely cheap, with some prescriptions costing just a few cents. Even if prices doubled, it may not drastically affect consumers. Specialty generic drugs, however, could see more noticeable price increases.

He also points out that if trade tensions extend to regions like the EU, India, or Japan, the situation could change. A broader trade conflict could influence drug prices, especially for certain medications. Overall, while tariffs on China may increase drug prices in the short term, the full impact will depend on the nature of global trade relations and the extent of supply disruptions.

Shehan also comments on how he believes the new administration will influence FDA approval processes for commercial products, other specific regulatory updates that drug developers should be closely monitoring in the current landscape, and much more.

How do you anticipate the evolving regulatory environment impacting the future of pharmaceutical development, especially in the context of emerging technologies like AI?

To me, AI is an extension of technology that already exists out there, an improvement. But, like in some other applications, I don't think it's as big a change, because people have been using advanced computing techniques in this area for quite a while. It'll be interesting if we're able to shorten development times. I think that can be very promising area.

Perhaps you're able to use AI to better define the patient populations that drugs should be tested in and approved for, so you end up in a world where you have more customized drugs, and perhaps those have a shorter development pathway and an approval process. That's pretty exciting. I go to conferences, and you hear a lot of talk about the possibilities. Now, we just need to kind of conceptualize them.

In the final part of his video interview with Pharma Commerce Editor Nicholas Saraceno, Jim Shehan, chair of the FDA regulatory practice at Lowenstein Sandler, explains how he anticipates the evolving regulatory environment impacting the future of pharmaceutical development, especially in the context of emerging technologies like AI.

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