Let's start with an alarming pair of statistics. First, 40% of specialty product prescriptions actually get filled, and second, when a patient’s copay or out-of-pocket cost exceeds $250, the abandonment rate is nearly 70%.

Pharmaceutical manufacturers are focused on making massive investments in product launches, field force training, marketing, and healthcare provider (HCP) education, but what happens to that momentum once the prescription is written and it is in the hands of the patient to fill? The disconnect in the level of pre- and post-prescription focus is easy to understand because the complexities of each require wildly different solution thinking. Across the specialty medicine market, we are seeing that unaddressed post-prescription issues have serious impact on patients, prescribers, and the pharmaceutical manufacturers that serve them.

Once a specialty prescription is written, fulfillment can become derailed at any number of points in the process. It can be helpful to look at these roadblocks and the key strategies for reducing or eliminating prescription abandonment under the framework of “the 4 Es”: enrollment, engagement, entry point (or access), and execution (or delivery).

Reducing friction in the hub enrollment process is the first step in helping patients get and stay on their therapy. Meeting HCPs in the electronic health record (EHR), where they spend a large percentage of their day, can vastly improve speed to therapy. Allowing HCPs to access key features and data without leaving their familiar in-EHR clinical workflow means they don’t have to switch between different applications, reducing the time to enrollment and the risk of data entry errors since the patient information is already there.

As non-commercial pharmacies (NCPs) are increasingly integrated into hub enrollment strategies, the EHR as a mechanism for enrollment is more common. For self-administered products covered under pharmacy benefits, including treatments such as oral therapies, self-injectables, and self-administered drugs, the NCP can serve as a valuable enrollment channel.

In these situations, HCPs don’t need to enter the patient data because it is already in the EHR, and the relevant information (i.e., diagnosis codes, demographic data, etc.) is automatically transferred to the prescription. In-workflow EHR prescribing can give patients access to the medication days or even weeks faster. The time HCPs would normally have spent dealing with enrollment can now be used where it belongs, with their patients.

In addition, digital portals can streamline documentation submission by providing a centralized platform where HCPs can upload, access, and manage patient information.

This eliminates the need for paper forms, manual data entry, and faxing—and ultimately leads to improved accuracy and communication.

Technological advances are helping put patients at the center of their care more than ever before, enabling them to become more actively involved in making decisions about their treatment instead of passively receiving care.

Among the tools that are available to patients are mobile-first solutions that can help boost adherence while giving pharmaceutical manufacturers more information about the types of support patients want most. Best-in-class offerings include text-to-enroll capabilities, digital communication channels for updates and reminders, and patient self-service options through mobile platforms.

Leveraging patients’ reliance on their phones as a first stop for information, mobile care platforms can connect in a single place the individual silos that are supporting them. Funneling everything through one service to keep patients well informed benefits not just them and HCPs, it also gives brands more leverage to incorporate the best option for each of those silos.

Engaging different generations of patients, including both digital natives, such as Gen Z and Millennials, and older generations, who are not as familiar with digital platforms, is an important aspect of a pharmaceutical manufacturer’s engagement strategy for their brands. To address the widest range of patient needs and preferences, an effective engagement strategy should incorporate both traditional and digital channels.

With prescription drug pricing as volatile as it is today, never has an access strategy been more important in helping patients start and stay on their medication. If they haven’t already, pharmaceutical manufacturers should develop comprehensive programs that make their brands available, affordable, and easily obtainable. 

An effective access strategy should include a number of key elements, including:

Effectively addressing prior authorizations (PA) denials. 

Pharmaceutical organizations should leverage technology, including electronic PA and real-time benefit verification systems to streamline processes; build strong relationships with payers; educate HCPs about specific PA requirements; and monitor denial trends—with the ultimate goal of minimizing the strain on HCPs and reducing speed to therapy for patients.

These programs often provide a lifeline for patients who otherwise cannot afford their prescribed medications. They deliver a temporary free supply of medication to the patients while hub agents work through coverage restrictions and then seamlessly transition the patient from bridge to commercial product once coverage is obtained.

 Seamlessly connecting a copay support program with a patient’s insurance plan allows the dispensing pharmacy to automatically calculate the patient’s out-of-pocket cost and apply the discounted price.

Developing a smart execution strategy that ensures patients receive and start therapy is critical to improving adherence. Providing patients with tools that allow them to track the progress of their prescription, including patient engagement platforms that feature “pizza tracker”-style visibility, offers ways to further engage patients in their own treatment. Offering visibility into the fulfillment process, not just for patients but for all stakeholders, can increase engagement, loyalty, and, ultimately, adherence.

Pharmaceutical manufacturers that place as much focus on their patients’ post-prescription journey as they do on pre-prescription brand marketing and sales efforts are likely to be rewarded with more engaged patients and increased adherence. Using the 4 Es as a framework for combating prescription abandonment, companies can evaluate their current approach and determine if changes need to be made. 

- Kristine McGaughey, Vice President, Implementation at ConnectiveRx, contributed to this article.

Chris Dowd is Senior Vice President, Market Development, at ConnectiveRx. With a nearly 30-year career spanning leadership roles across Big Pharma, healthcare startups, and the patient support space, Dowd is a preeminent industry voice in patient access and adherence.

Articles

The key strategies for reducing or eliminating post-prescription abandonment.

From Prescription to Patient: Four Ways to Increase Speed to Therapy 

One of the objections I sometimes hear when discussing counterfeiting and diversion challenges with pharmaceutical manufacturers, particularly smaller ones, is that they just don’t know enough about the problem. They may suspect they have a problem and/or they may have seen some evidence of a problem, but they feel they lack sufficient data or knowledge to take concrete steps to address it—beyond doing the minimum required by law, of course, such as serialization. This knowledge gap may also lead them to conclude that even if a problem exists, the risk is likely to be low, and additional investment in product integrity is not warranted.

My response to this challenge is always that you probably know more than you think—you just need to know where to look. And, as for the risk, it may be greater than you perceive it to be—for your patients, your reputation, and your business. My best advice is to take proactive steps to gather the available data, which will enable you to better understand the issue and make an informed decision about what illicit trade risk management should entail for your business.

How do you know more than you think? Because your existing internal data and business intelligence, when viewed through a product integrity lens, can provide a trove of relevant and useful information. Digging into this data can begin to shed light on the issue and provide actionable insights. Your colleagues working in the commercial, quality, and supply chain areas may also be able to provide valuable information to help you begin to formulate a clearer picture of the risk. Consider the data sources in the below table and what they can tell you about illicit trade risk (click to enlarge). 

Knowing where to look and what the data can potentially reveal is, of course, just the first step on your data-driven journey to becoming better informed about illicit trade risk. Armed with a list of the relevant data sets and the questions you’re trying to answer with the data, that’s when you invite your data and analytics team to the table. They’ll need to understand the problem you’re trying to solve, then prepare the data and apply the appropriate analytical tools and techniques, such as machine learning, natural language processing, statistical analysis, and AI techniques, to obtain answers and actionable insights that will inform your decision-making.

The global threat of illicit trade continues to grow every year. If you wait to take additional preventive measures until a counterfeit product turns up online or in your legitimate supply chain, then it’s probably too late. It’s a lot more challenging to be in a reactive mode, trying to address patient safety and customer concerns, versus taking proactive steps now to conduct a rigorous assessment, followed by an informed leadership decision about what level of risk is acceptable and implementing a program that meets your objectives. It’s a risk you can’t afford to ignore.

Sean O’Hearen is Founder and Principal Consultant at 1st Line Partners.

Why taking proactive steps—and combing the right data sources—is critical to informed decision-making in risk management.

What Your Data Can Tell You About Illicit Trade Risk

Healthcare costs, insurance barriers, and medical debt are preventing patients with chronic illnesses in the US from accessing essential treatments and medications. That’s according to the PAN Foundation’s Center for Patient Research State of Patient Access Report initiative.

, released in March, found patients living with chronic health conditions rated the overall state of healthcare access a C (75.2). Overall, more than one in five patients reported that prescriptions are not affordable (23%), and they find it difficult to pay for drugs (22%). In addition, a quarter of patients (25%) said their lives are greatly impacted by the financial toxicity of healthcare costs. It’s clear that change is needed.

Launched in 2024, the State of Patient Access Report gathers insights directly from adults with chronic health conditions through a nationwide survey conducted by The Harris Poll. Survey results are then synthesized and organized across five categories to develop an annual scorecard. Scores are calculated for the total patient population and for various subgroups to identify disparities in access to care.

In addition to an overall score,the 2025 report also highlights the aggregate scores for each category:

Relationship with healthcare professionals = B (84.3)

Affordability of prescription medications = B- (80.8)

Access to treatment through healthcare plans = D- (63.1)

1. Healthcare access and affordability isn’t getting better.

 Compared to the 2024 report, this year’s survey shows little progress in patient access. Most composite measures did not move materially between 2024 and 2025, with affordability of prescription drugs and financial toxicity declining. 

2. Having health insurance does not guarantee access.

Once again, access to treatment through healthcare plans earned a “D-,” the lowest overall grade across all categories. The score fell to an “F” for American Indian/Alaska Native, Hispanic, and LGBTQIA+ patients, highlighting continued differences in health outcomes.

3. Prescription affordability continues to be a challenge.

The Rx affordability score dropped from 82.3 in 2024 to 80.8 this year. Overall, 22% of patients struggled to pay for prescriptions, and 21% could not access needed medications due to cost.

4. Financial toxicity remains a serious issue for many.

 Sentiment fell to a “D+”, from a “C-” in 2024, with 25% of patients significantly affected by healthcare costs. Over half (56%) of LGBTQIA+ respondents reported high financial toxicity, nearly double that of non-LGBTQIA+ respondents (24%).

5. Medical debt is a leading concern among patients. 

New to this year’s report, questions related to the negative impacts of medical debt were included. Two in five respondents (40%) reported having medical debt, with an average of $729. Notably, medical debt is unevenly distributed, with patients of color averaging $983 in debt compared to $584 for patients identifying as white.

This year’s findings show that healthcare access remains a significant challenge for many Americans and there is urgent need for lasting policy solutions. Groups such as the PAN Foundation remain committed to working with policymakers, patients, healthcare professionals (HCPs), and patient advocacy organizations to help break down access barriers.

But we also encourage individual action in this effort, which could look like:

Contacting your policymakers to share your story and ask them to prioritize policies around access and affordability.

As patients, educating yourself about how to better navigate your healthcare journey and available resources.

As HCPs, talking with patients about their access and affordability challenges.

As patient advocacy organizations, keeping abreast of evolving patient opinion and experience, to further emphasize the access challenges they face.

Amy Niles is chief mission officer at PAN Foundation.

1. 2025 State of Patient Access Report. PAN Foundation. 

https://www.panfoundation.org/state-of-patient-access

A look at the prevailing factors impacting treatment access in 2025.

Healthcare Scorecard from Patients with Chronic Illness

Welcome to the third installment of my “Popping the Gross-to-Net Bubble” series. In my previous column, I explored actionable steps pharmaceutical manufacturers can take to address gross-to-net (GTN) challenges for products reimbursed under the medical benefit. This time, I focus on products reimbursed under the pharmacy benefit.

The complexity of gross-to-net in the pharmacy benefit

Managing GTN for the pharmacy benefit is significantly more complex than for the medical benefit, due to its wide variability across payer types and product archetypes.

Payer types include commercial, Medicare, Medicaid, health maintenance organizations (HMOs), 340B, and government accounts, such as the VA, DoD, and Indian Health Service, while product archetypes feature general medicine brands, generics, vaccines, specialty lite, specialty, specialty generics, biosimilars, and orphan/rare products.

From our 24 years of experience working with pharmaceutical companies, we’ve seen many new product planning, pricing, and market access teams prioritize large commercial pharmacy benefit managers (PBMs) first, as they cover the most lives. However, the focus is typically on achieving formulary coverage rather than optimizing net revenue—a key driver of poor GTN performance.

Instead, we recommend starting with statutory discounts such as Medicaid unit rebate amount (URA), 340B, and Federal Supply Schedule (FSS), as they are fixed costs that can significantly impact GTN if not properly managed in relation to commercial payer decisions.

Let’s examine how GTN varies between two contrasting product types: general medicine brands and orphan/rare brands.

The two examples at right (click to enlarge) represent the GTN spectrum. Other product types such as specialty and specialty lite drugs fall somewhere in between, depending on factors such as budget impact analysis, payer contracting, clinical profile, and access restrictions (e.g., step edits, prior authorization, catastrophic coverage, etc.).

Key components of GTN and manufacturer strategies

Pharma manufacturers must navigate six key GTN components when planning for pharmacy benefit reimbursement:


Manufacturers should start with statutory discount analysis based on channel and payer mix. Products sold to government accounts (Medicaid, Medicare, VA, DoD, Indian Health Service, etc.) are subject to mandatory rebates, which must be accounted for upfront.


After assessing statutory discounts, manufacturers determine PBM and HMO rebates and admin fees. These discounts directly impact formulary positioning, patient access, and out-of-pocket costs. However, the net pricing decisions here will also influence statutory discount liabilities, making this a critical risk area.


Manufacturers must consider whether discounts should be extended to sites of care (e.g., hospitals, infusioncenters) either directly or via GPO contracts. Pre-formulary coverage discounts may help drive early adoption. Additional discounts for outpatient pharmacies typically apply only to long-term care facilities or hospital-affiliated GPO networks.


Prompt pay discounts vary by distributor type. Additional fees beyond bona fide FFS depend on manufacturer size, portfolio breadth, and time on market. Many emerging manufacturers are now bypassing wholesalers and selling directly to sites of care to reduce excessive distribution costs.


Traditionally designed and directed by marketing or brand teams, patient support programs are often finalized after PBM negotiations. Manufacturers have historically aimed for $0 to $35 copays for commercially insured patients, but this strategy needs reevaluation as Medicaid copays cannot be bought down; Medicare OOP costs are now capped at $2,000 annually (effective 2025); copay accumulator and maximizer programs limit the effectiveness of affordability programs; and manufacturers are becoming more strategic about applying affordability support to avoid wasted resources.

6. Penalty discounts & price increase strategy


Price increases must be carefully planned due to rebate penalties from Medicaid and Medicare. Outpacing the consumer price index results in perpetual penalties, impacting 55% of the pharmacy benefit market represented by Medicaid and Medicare collectively. The removal of the average manufacuter’s price (AMP) cap (effective Jan. 1, 2024, under the American Rescue Plan Act of 2021) has led some manufacturers to exit Medicaid due to negative GTN scenarios. Manufacturers must align pricing strategy with GTN management to avoid unintended financial consequences.

The key to managing GTN: Strong cross-functional governance

Pharma companies that effectively manage GTN integrate finance and government pricing teams into decision-making alongside marketing, field sales, market access, trade and distribution, and patient services. Conversely, companies that struggle with GTN allow each of these groups to operate independently, with finance and government pricing teams relegated to support roles rather than strategic partners.

As pricing pressures increase under the IRA and Medicaid AMP cap removal, we anticipate finance and government pricing teams will play an even greater role at the executive level.

In my next installment, I’ll examine examples of how pharmaceutical manufacturers have successfully and unsuccessfully navigated GTN challenges. I’ll highlight common pitfalls and lessons learned that can help manufacturers avoid costly mistakes.

Bill Roth is General Manager and Managing Partner of IntegriChain’s consulting business, which includes Blue Fin Group, a strategy consulting company he started in 2001, and the IntegriChain advisory services business.

How pharma manufacturers can steadily navigate GTN components and                                             complexities when planning pharmacy benefit reimbursement.

Popping the Gross-to-Net Bubble, Part III: The Pharmacy Benefit

, I felt that various recent developments were worth noting, considering the impact they could have on the US prescription drug market. They include the drug industry's push to make Inflation Reduction Act (IRA) changes to the “pill penalty” and negotiation eligibility timing for orphan drugs, along with President Trump’s executive order to reinforce transparency rules for prescription drugs. These are detailed further ahead.

The Centers for Medicare & Medicaid (CMS) Services price negotiations under the IRA involve a selection of eligible Rx drugs that have the highest Medicare budget impact. Small molecules become eligible for negotiations nine years after the first launch of the molecule, whereas biologics have a 13-year grace period. The earlier eligibility for small molecules—a four-year difference—is often referred to as the “pill penalty.” Taking four years off the highest revenue-producing years away from drugs that typically also decline much faster in revenue upon patent expiration is heavily impacting the financial viability of small molecule development in comparison with biologics. The drug industry is pushing for an elimination of the pill penalty, making small molecules eligible for negotiation after 13 years as opposed to nine. They also ask to only start the clock for negotiation eligibility for orphan therapies after the drug loses its orphan drug exclusivity status.

Meanwhile, the industry is arguing that CMS should negotiate separately for drug use under a new formulation or indication. Industry association PhRMA argues that CMS’s interpretation of the IRA—which is to set prices for drugs based on their active moiety or active ingredient—is overly broad.

The industry is hoping to include the mentioned changes in the reform package that Congress is currently considering. However, the additional cost of these changes will certainly be weighed against the Trump administration’s ambitious plans to extend the 2017 tax cut, tackle immigration, and provide additional defense spending. It seems as though the Trump administration is unlikely to prioritize CMS price negotiation reform over tax reform objectives, as there is little room to maintain budget neutrality and avoid a need for a 60% majority requirement in Congress.

IRA’s impact on availability of new treatments will likely not be clear for another few years, as the portfolio of negotiated drugs is expanding and the impact on company decision-making regarding R&D will become clearer. The mechanism of IRA drug negotiation selection has already resulted in a deprioritization of small molecule (oral) drugs, along with a delay of launch for smaller patient populations with higher medical unmet need until the uses for larger patient populations are ready for FDA approval and commercialization.

Trump signed an executive order (EO) on Feb. 25 that reinforces healthcare price transparency rules that were first issued in 2019, but that were not prioritized for implementation by President Biden. The new EO makes specific reference to drug pricing: “… fully enforce my Administration’s requirement that would end the opaque nature of drug prices by ensuring health plans publicly post the true prices they pay for prescription drugs.” Furthermore, the EO emphasized: “the old directive also required health plans to post their negotiated rates with providers, as well as their out-of-network payments to providers and the actual prices they or their pharmacy benefit manager pay for prescription drugs.”

The new EO may have some far-reaching implications for the drug industry. Transparency of negotiated drug prices will change the dynamics of negotiations with pharmacy benefit managers and managed care plans. It is my belief that all major drugmakers carefully manage the consistency of rebate terms across their customers, but having all prices across customers publicly displayed can intensify the competitive dynamic and force an even higher level of discipline than currently employed. It does not seem that the EO applies to 340B prices and confidential state Medicaid prices such as under California’s MediCal, which would bring further complications.

The EO offers some great opportunities for the industry to bring transparency to levels of patient copayments in relation to the actual drug cost to health insurance plans. It will offer opportunities to highlight the cases where payers are using patient copayments to generate additional profits.

Ed Schoonveld is a value and access advisor for Schoonveld Advisory and author of The Price of Global Health.

1. Kelly C. IRA Negotiation Changes: Pharma’s Focus Remains On Near-Term Legislative, Regulatory Options. 

https://insights.citeline.com/pink-sheet/market-access/government-payers/medicare/ira-negotiation-changes-pharmas-focus-remains-on-near-term-legislative-regulatory-options-5AJDYB6SWNGVBLOO6KHTLJ3KQA/?utm_source=RSS_feed&utm_medium=twitter&utm_campaign=PinkSheet

Respective industry and government agendas could significantly reshape the US prescription drug market.

US Drug Price Negotiations and Transparency

In today’s healthcare landscape, groundbreaking treatments such as cell and gene therapies, mRNA vaccines, and GLP-1 drugs are transforming patient care. At the same time, essential medications remain vital for treating a wide range of conditions. Ensuring these treatments reach patients safely and efficiently is crucial—and can be accomplished by modernizing, future-proofing, and securing the healthcare supply chain.

We envision the supply chain of the future as an interconnected network of both physical and digital assets, not merely a series of transactions. Modernizing our supply chain is key for enhancing efficiency, visibility, and infrastructure. In recent years, we have embraced digital enablement to optimize our operations by integrating artificial intelligence and machine learning across our healthcare ecosystem. This has allowed us to optimize logistics, including transportation routes and delivery schedules, thereby reducing costs and improving efficiency. The goal is to ensure that our supply chain remains efficient and adaptable to future challenges.

In the everchanging pharmaceutical landscape, the advancement of medical treatments, including drugs for rare diseases and specialty therapies, offers great promise and hope. It’s vital that our supply chain provide these crucial therapies safely and efficiently.

Specialty therapies often require specific conditions, such as temperature control and light protection, necessitating robust infrastructure and meticulous management. Additionally, many new medicines have shorter shelf lives, requiring precise inventory management to prevent stockouts and expirations, so in order to meet this growing demand, we encourage stakeholder to consider expanding cold chain storage, infrastructure, and quality controls.

The commitment to those we serve drives us to uphold stringent safety and security standards, maintaining a rigorous chain of custody from manufacturer to patient. The Drug Supply Chain Security Act (DSCSA) is designed to protect US consumers by securing the supply chain against counterfeit, contaminated, or harmful drugs through electronic traceability mandates. Over the past decade, we have actively engaged in industry readiness for DSCSA serialization compliance, and we continue to advance our preparedness as we near the May 27 compliance deadline for wholesale distributors.

The industry has developed and implemented various track-and-trace technologies to comply with the DSCSA and to enhance the security and integrity of the pharmaceutical supply chain. These technologies include serialization, which assigns unique identifiers to prescription drug packages, and real-time tracking, allowing continuous monitoring of product location and status. 

Together, these innovations provide comprehensive visibility and control, safeguarding against counterfeit drugs and maintaining product integrity.

Ammie McAsey is SVP of Customer Distribution Experience at McKesson.

Ensuring that essential treatments reach patients safely and efficiently is an increasing imperative in today's pharma landscape.

Strategies to Modernize, Future-Proof, and Secure the Healthcare Supply Chain

Developing effective lifesaving drugs requires significant research and development (R&D) investments. New medications cost an average of $2.3 billion to develop,

 largely funded by existing drug sales. At the same time, pharmaceutical companies are under increasing pressure from the government to reduce prescription prices, which presents a significant hurdle to maintaining the R&D pipeline.

Industry leaders and economic experts are concerned that the Inflation Reduction Act (IRA),

 with its price negotiations and caps, could further stifle research investments. According to Model N’s 2025 State of Revenue Report,

 nearly two-thirds of pharmaceutical leaders are worried about how the IRA will impact their pricing strategies.

Pharma manufacturers must adjust legacy pricing processes to maintain medication access while still supporting drug development. While difficult, this is doable. Effective revenue management and artificial intelligence (AI)-powered data analysis can help manufacturers navigate the pricing pressure.

Under the IRA, pharma manufacturers must negotiate Medicare drug prices for specific medications with the federal government. The parties reached an agreement on the first 10 drugs in 2024, and the Centers for Medicare and Medicaid Services announced the next 15 drugs up for negotiation earlier this year,

 which includes revenue-driving GLP-1s. The larger number of drugs included in the second set signals the federal government’s intent to accelerate cost reductions across a broader spectrum of therapeutic areas.

In addition to price negotiations, the IRA requires manufacturers to pay rebates to the government if they raise drug list prices faster than inflation, and it caps out-of-pocket expenses for Medicare recipients.

Some experts and industry leaders worry these provisions could potentially have a chilling effect on R&D in several ways:

The IRA’s pricing actions will likely compress revenue streams and reduce capital for R&D investments. After Medicare-negotiated prices take effect, manufacturers lose pricing flexibility, resulting in lower revenues for products that traditionally help fund research for new therapies. Inflation price caps restrict manufacturers’ ability to offset increasing operational costs. Maintaining compliance also requires dedicated resources that could detract from research initiatives. Research from the University of Chicago estimates IRA provisions could lead to a 31% decrease in pharmaceutical revenues through 2039 and result in 135 fewer drug approvals.

The price limits may discourage companies from pursuing new therapies, particularly those targeting Medicare beneficiaries. The potentially low—or even negative—return on investment makes R&D difficult to justify fiscally. With reduced revenue certainty, manufacturers may deprioritize high-risk or long-term projects, focusing instead on safer or more immediately profitable therapeutic areas.

The reduced incentive is particularly pronounced for biosimilar and generic development. If government negotiations significantly reduce brand-name drug prices, the profit margin for potential generic and biosimilar versions also drops. Combined with rebate structures that favor brand names, spending time developing and launching these lower-cost alternatives may not make financial sense.

The IRA's negotiated prices cover all of a drug’s indications, regardless of when the new uses are approved. This means pharma manufacturers cannot price the drug differently for the new treatment, further limiting their ability to recoup research investments. Additionally, a drug with multiple indications may attract government interest in negotiations more so than one with a single therapeutic use.

These factors disincentivize post-approval research, resulting in fewer treatment options for patients and curtailing evidence generation to track long-term health outcomes. Postmarketing studies generate more than just new indications; data from these kinds of studies demonstrates a drug’s safety and efficacy and informs prescribing practices. Research in 

demonstrates the IRA’s potential impact on this research.

 The market uncertainty generated by the IRA increases financial risks and complicates forecasting. If manufacturers don’t know which drugs will be included in future negotiations, they can’t predict revenue or prioritize research areas. The IRA also shortens the period during which manufacturers can charge market-driven prices, forcing companies to estimate the value of a drug over a shortened time frame. Pharma companies may hesitate to pursue long-term projects if they can’t accurately assess potential returns.

After just one year of negotiations, the IRA is already impacting pharma companies’ strategies. In Model N’s aforementioned State of Revenue Report, 87% of surveyed executives say they’ve already altered their launch plans for specific diseases or therapeutic areas.

Reducing the costs of R&D is difficult given the focus on safety, increasing sophistication of modern therapies, and specific requirements for FDA approvals. Despite scientists’ best efforts, many new compounds fail, and the ones that succeed often take years or even decades to bring to market.

 However, there are some reasons to be hopeful.

AI-powered drug discovery may soon expedite research timelines and reduce development costs. AI technologies enable comprehensive analysis of vast molecular databases to identify the most promising compounds, reducing failure risks and accelerating preclinical timelines. Additionally, genomic analysis and sequencing innovations will enable researchers to identify disease targets and biomarkers for more precise therapies.

Advanced analytics can enhance data quality by identifying ideal clinical trial candidates, quickly evaluating trial outcomes and monitoring adverse events. The result is more effective medications delivered quickly, increasing revenue opportunities.

However, these technologies are relatively new and require investments to implement. In the meantime, pharma manufacturers must overhaul their revenue management processes to maintain funding for drug R&D in this new pricing environment.

Enhancing revenue management processes to protect R&D

Legacy pricing strategies will no longer suffice for pharma companies under pressure for the IRA. They must improve their data gathering, aggregation, and analysis to develop optimized pricing tactics while also reducing revenue leakage.

Successful data analysis requires manufacturers to break down organizational silos and incorporate external sources to obtain and consolidate data from drug portfolios; R&D efforts; current contracts; sales; the supply chain; and competitor prices, along with market preferences and trends.

Manual data gathering no longer suffices in the complex market. Pharma companies should invest in automation to ensure they have comprehensive, current, and actionable data. AI-powered platforms can analyze this information to model different scenarios, such as the impact of IRA price negotiations on revenue, inflation penalties on Medicare segments versus commercial market revenue, rebate strategies for maintaining market access, and gross-to-net implications across different payer channels.

Such insights can inform launch and pricing strategies to maintain market access and margins. In many cases, success may require sophisticated rebate and contracting approaches. A robust revenue management platform enables manufacturers to develop optimal structures and accurately calculate rebates and payments to avoid unnecessary losses.

While the IRA’s long-term impacts on pharma manufacturers are yet to be seen, maintaining market access for drugs and R&D funding will be a delicate balance over the next few years. These companies will need to complement new R&D strategies with more nuanced pricing strategies to continue the steady development of new lifesaving drugs.

By integrating advanced analytics and AI-driven tools into their revenue management processes, manufacturers can anticipate market changes, mitigate regulatory risks, and optimize their portfolios while continuing to support innovation. More efficient and effective revenue management processes will shore up income to support short-term revenue goals while continuing to fund the long-term development efforts that both patients and the industry depend on.

Jesse Mendelsohn is a senior vice president at Model N, a revenue optimization and compliance provider for life sciences and high-tech companies.

1. Deloitte Pharma Study: R&D Returns are Improving – Regulation Could Stifle Innovation. Deloitte. June 24, 2024. 

https://www.deloitte.com/ch/en/about/press-room/deloitte-pharma-study-r-and-d-returns-are-improving.html

2. Inflation Reduction Act and Medicare. CMS.gov. 

https://www.cms.gov/inflation-reduction-act-and-medicare

3. 2025 State of Revenue Report. Model N. 

https://www.modeln.com/state-of-revenue-report-2025/

4. HHS Announces 15 Additional Drugs Selected for Medicare Drug Price Negotiations in Continued Effort to Lower Prescription Drug Costs for Seniors. CMS.gov. January 17, 2025. 

https:// www.cms.gov/newsroom/press-releases/hhs-announces-15-additional-drugs-selected-medicare-drug-price-negotiations-continued-effort-lower

5. Philipson, T.J.; Durie, T. The Impact of HR 5376 on Biopharmaceutical Innovation and Patient Health. The University of Chicago. November 29, 2021. 

https://cpb-us-w2.wpmucdn.com/voices.uchicago.edu/dist/d/3128/files/2021/08/Issue-Brief-Drug-Pricing-in-HR-5376-11.30.pdf

6. O’Brien, J.M.; Motyka, J.; Patterson, J.A. How the IRA Could Delay Pharmaceutical Launches, Reduce Indications, and Chill Evidence Generation. 

https://www.healthaffairs.org/content/forefront/ira-could-delay-pharmaceutical-launches-reduce-indications-and-chill-evidence

7. Van Norman, G.A. Drugs, Devices, and the FDA: Part 1: An Overview of Approval Processes for Drugs. 

https://doi.org/10.1016/j.jacbts.2016.03.002

How data-driven insights can help pharma companies balance their revenue management and innovation strategies—including resource allocation, pricing, and market access.

Maintaining R&D Investments in the IRA Era

The COVID-19 pandemic highlighted our supply chains’ weaknesses like never before. A sudden surge in demand and limited production capabilities led to critical shortages of medical supplies, pharmaceuticals, and even basic consumer goods. For life sciences, this disruption wasn’t just a matter of lost revenue—it was a matter of life and death. In this high-stakes industry, we need systems that adapt, predict, and respond to change faster than ever before.

At the same time, the manufacturing sector is facing another growing challenge: a shortage of skilled labor. Many life sciences manufacturers struggle to fill critical roles, from production technicians to quality control specialists, putting even more pressure on a strained supply chain.

This is where generative artificial intelligence (GenAI) emerges as a transformative force. GenAI offers the tools to bridge the talent gap, serve as a knowledge base for manufacturing teams, and help stabilize production by optimizing processes, predicting disruptions, and ensuring the consistent delivery of life-saving treatments. But its impact isn’t theoretical; it’s measurable and already reshaping the industry.

The pandemic taught us that being reactive isn’t enough. To avoid catastrophic disruptions, we need proactive tools that allow for real-time adjustments. GenAI provides precisely this, enabling companies to model scenarios, forecast potential disruptions, and adjust production plans based on real-time factors. For example, a pharmaceutical company producing a critical diabetes medication in a hurricane-prone region could use GenAI to analyze historical weather patterns, including hurricane data, and predict potential disruptions to their raw material supply. The system could then recommend alternative sourcing options or suggest increasing production aheavd of hurricane season to build a safety stock. The power of GenAI lies in its ability to analyze enormous datasets, from weather patterns to geopolitical events, and predict supply chain impacts before they even occur.

In 2020, the estimated global cost of supply chain disruptions reached $4 trillion,

 underscoring the urgent need for resilience. Imagine a future where pharma companies, by analyzing weather data and historical demand, can foresee a delay due to a hurricane and shift manufacturing schedules accordingly. This kind of agility and foresight is what GenAI brings to the table, and it’s increasingly becoming essential in a volatile world.

At first glance, the world of life sciences may seem far removed from consumer goods. But, surprisingly, the challenges in quality control and transparency are strikingly similar. When we buy a product, whether it’s makeup or shoes, we can track its journey from the warehouse to our door. This visibility builds trust and empowers consumers with knowledge about their purchase’s journey.

For life sciences, having clear transparency could be game-changing. Imagine a scenario where patients, providers, and regulators could monitor a medication’s production journey, from raw material sourcing to final quality checks. With GenAI-driven transparency, life sciences companies can create this level of visibility, streamlining compliance and boosting patient confidence. Regulatory bodies also benefit from this clear line of sight, which supports faster, data-driven oversight and enhanced accountability.

GenAI further amplifies quality control, performing visual inspections that detect inconsistencies with greater accuracy than manual methods. It’s a level of detail and precision crucial to life sciences, where the slightest error could have life-altering consequences. For example, in 2021, the FDA flagged almost 1,300 drug quality issues related to production inconsistencies,

 which GenAI-powered quality checks could have minimized or prevented.

Beyond detection, AI can also predict and address quality control challenges by analyzing process deviations and recommending corrective actions in real time. This capability ensures consistent product quality and helps manufacturers comply with stringent regulatory standards.

Generative AI’s impact on life sciences manufacturing is tangible. Here are some ways it’s already transforming the field:

Say goodbye to unexpected equipment breakdowns. 

In traditional manufacturing, unexpected equipment failures can halt production, leading to costly delays. By analyzing process data, GenAI anticipates when machinery needs maintenance, reducing unplanned downtime. This capability is already saving companies millions in preventing disruptions. Imagine a pharma manufacturer using GenAI to monitor their sterile filling line could analyze sensor data (e.g., temperature, pressure, vibration) to predict when a filling nozzle will likely clog. This proactive maintenance approach prevents costly downtime and ensures continuous production of sterile injectables.

 Digital twins, virtual replicas of supply chain networks, enable companies to simulate disruptions and test responses. According to McKinsey & Company, digital twin technology can reduce supply chain costs by 10% and improve product launch success by 20%, making it a powerful tool for life sciences.

GenAI’s ability to analyze patient-specific data is paving the way for highly personalized treatments. Drug formulation, for instance, tailors dosages to optimize patient outcomes, which is especially valuable in chronic disease management where personalized care is essential. GenAI can analyze historical production data, raw material characteristics, and environmental factors within a manufacturing facility to optimize the production process for a specific drug formulation. GenAI ensures consistent quality and higher yields by adjusting parameters such as temperature, mixing speed, or drying time.

Automation of remediation for adverse effects.

 Drugmakers often submit 10,000+ pages of reports on adverse effects to the FDA. GenAI can automate this process, reducing manual effort, improving accuracy, and accelerating regulatory approvals.

GenAI’s promise comes with challenges. The regulatory environment remains complex, as bodies like the FDA establish frameworks to ensure safe and effective AI use. In 2023, the FDA released guidance on AI transparency, signaling that the technology’s growth must be matched by rigorous oversight. Life sciences companies must stay ahead of these changes to implement GenAI responsibly.

Data quality is another critical factor. GenAI’s success depends on reliable, high-quality data, yet a recent McKinsey survey found that more than 60% of companies cite data quality as a major challenge in implementing AI.

 Life sciences organizations need robust data management strategies to fully unlock GenAI’s potential.

Finally, there’s the challenge of a talent gap. GenAI requires a specialized skill set at the intersection of life sciences and data science, and competition for this talent is fierce. Life sciences companies will need to invest in both recruitment and training to build the expertise necessary to leverage GenAI effectively.

The potential of GenAI in life sciences manufacturing is vast. In the future, partnerships between technology providers, healthcare, and life sciences companies will be essential for driving AI innovations forward. Increased collaboration will encourage transparency and data-sharing practices, which are crucial for regulatory support and oversight.

The ongoing talent gap in manufacturing is another factor that will shape AI adoption. As the industry faces a shortage of skilled workers, GenAI can act as a knowledge base, preserving institutional expertise and guiding new workforce entrants in complex manufacturing processes. AI-powered decision support systems will enable companies to maintain high production standards even as labor shortages persist.

As GenAI becomes more integrated into manufacturing, we’ll see costs decrease, benefiting patients and end-users alike. In a future crisis, real-time optimization could prevent the kind of shortages we saw early in the pandemic. For example, if another global event disrupts supply chains, GenAI can dynamically adjust production schedules, recommend alternative suppliers, and balance inventory levels to maintain a steady supply of essential goods.

GenAI is paving the way for a resilient, responsive healthcare ecosystem built on innovation and accessibility. The journey ahead holds incredible promise, and life sciences is on the brink of an essential and inspiring transformation.

Shweta Maniar is the Director of Global Healthcare & Life Sciences Industry Strategy at Google Cloud

1. The Aggregate Effects of Global and Local Supply Chain Disruptions: 2020–2022. World Bank Group. February 13, 2023. 

https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099358202132331977/idu04fa983470a55e045cf086ea01ed3050976da

2. Drug Shortages for Calendar Year 2021. FDA. 

https://www.fda.gov/media/159302/download

3. Taking the Pulse of Shifting Supply Chains. McKinsey & Company. August 26, 2022. 

https://www.mckinsey.com/capabilities/operations/our-insights/taking-the-pulse-of-shifting-supply-chains

4. How COVID-19 is Reshaping Supply Chains. McKinsey & Company. November 23, 2021. 

https://www.mckinsey.com/capabilities/operations/our-insights/how-covid-19-is-reshaping-supply-chains

Taking stock of today's gains and tomorrow's potential for generative artificial intelligence in reshaping the industry.

Pharmaceutical Commerce - April 2025