Advanced technologies, rapid therapeutic modality innovations, pricing pressures, evolving collaborations, and novel pharmaceutical facility design approaches are some of the phrases that pop to mind when considering the pharmaceutical industry’s future success. Due to the global importance of the pharmaceutical industry to human health and economic prosperity, each of these concepts merits considerable thought.
The global pharmaceutical market is estimated at $1.6 trillion and serves billions of patients worldwide. Although the industry is healthy by many measures –– boasting a 6.15%1 estimated compounded annual growth rate, for example –– factors like inflation, government price controls, escalating competition, and disruptive technologies provide challenges and opportunities.
Pharma spending is rising, given the shift toward expensive specialty drugs and increasing global populations. Therefore, governments are implementing price control policies to manage costs, such as the U.S. Inflation Reduction Act (IRA). This bill, passed in August 2022, allows Medicare, the largest prescription drug payer in the world, to negotiate prices for some drugs directly. However, attempts to constrain drug pricing in the United States are raising concerns about reduced pharmaceutical R&D investment, potentially impacting innovation worldwide. But could these additional pricing controls force earnest dedication to R&D and operational efficiency progress?
While there are many unknowns when speculating the future of pharma, there is one certainty within the industry’s bright future — collaboration and the exchange of ideas. Some collaborations involve transformative advanced technologies, others with contract services organizations or facility design partners. Yet other advancements will be made by integrating increasingly diverse modalities into the industry’s therapeutic solutions offerings.
Human and Artificial Intelligence Align to Advance Progress
Artificial Intelligence (AI) profoundly contributes to virtually every area of the pharmaceutical industry, from drug discovery to supply chain optimization. While the usage of AI in the pharmaceutical industry is in its infancy, and there are challenges to address, AI's ability to advance the industry for the betterment of human health is undeniable.
Specifically, AI is outstanding at efficient data analysis, pattern recognition, deviation identification, and automating repetitive tasks. These strengths are quite helpful for drug discovery, development, process development, manufacturing, supply chain optimization, and clinical pharmacology research.
Drug Discovery
AI technologies can efficiently analyze disparate data types and sources, such as genetic, proteomic, and clinical data, to identify disease-associated targets and molecular pathways. Additionally, AI enables the efficient screening of enormous chemical libraries to narrow potential drug candidates.
Another contribution to the drug discovery process is efficiently optimizing therapeutic candidates. AI algorithms can evaluate numerous factors, such as safety, efficacy, and pharmacokinetics, helping researchers identify and advance the best candidates.
Finally, some pharmaceutical organizations own a multitude of molecules that never made their way to market. AI is proving useful in analyzing biomedical data to identify archived molecules that may have therapeutic potential.
Pharmacokinetic Evaluation
AI-enabled computational models can appraise complex molecular information, patient data, and pharmacokinetic data studies to predict drug behavior and advance the most promising constructs.
Process Development
Design of experiments (DoE) has been the foundation of pharmaceutical process development for decades. However, the complicated design spaces required for today’s complex drugs typically require an unwieldy number of experiments when using purely statistical models. Also, linear traditional DoE models are often insufficient in assessing the non-linear complexities of bioprocesses. Machine learning and AI technologies facilitate non-linear models to more accurately understand complex dynamics with fewer experiments.
Pharmaceutical Manufacturing
The ability to analyze and integrate data from process sensors and equipment makes AI-enabled technologies excellent process monitoring and optimization tools. Process engineers can improve product quality and operational efficiencies by identifying potential issues in real time.
“The integration of predictive modeling into bioprocess automation and control systems is transforming the biopharmaceutical industry, enabling enhanced performance and precision,” stated Sangmin Paik, Ph.D., Lead Engineer in Digital Excellence, Samsung Biologics. “By combining mechanistic models — such as hydrodynamic and cell kinetic equations — with data-driven insights and predictive algorithms, digital twins provide real-time simulations of cell growth, nutrient consumption, hydrodynamic behavior, and other critical variables.”2
Quality Control
Although there are numerous AI applications in quality control, one example is detecting tablet defects. AI algorithms combined with computer vision technologies analyze tablet images, automating the identification of defects like cracks, chips, discoloration, or irregularities in shape and size. By training on data sets of labeled images, AI models learn to classify and detect various defects with high precision and recall, ensuring more efficient and accurate quality assurance.
Supply Chain Optimization
Using AI-enabled algorithms to predict demand, supply chain professionals optimize inventory management, manufacturing schedules, storage, and distribution.
Pharma 5.0 Supports the Next Leap Manufacturing and Operational Advancements
A concept introduced in 2017 by the International Society of Pharmaceutical Engineering (ISPE), Pharma 4.0TM directed the Industrial Internet of Things (IIoT) to the specific needs of modernizing pharmaceutical production. It called for integrating digital technologies, automation, and data analytics across the pharmaceutical value chain to improve operational efficiency.
Pharma 4.0 focused on applying sensors, automation, connected equipment, and analytics to achieve smarter manufacturing, predictive maintenance, automated quality control, and numerous other advancements. While the industry made progress under the foundations of Pharma 4.0, rising costs and downward pressures on drug pricing require additional steps.
Pharma 5.0, a construct embraced by leading pharmaceutical organizations such as Pfizer, put humans back in the center by shifting the focus from pure automation to human–AI collaboration. “Although leveraging digital technologies such as optimizing processes, managing replenishment cycles, and shortening lead times can significantly enhance cycle time, titers, and yields, human expertise plays a crucial role in Pharma 5.0,” commented Tom Wilson, Global Contract Manufacturing Lead at Pfizer CentreOne, “It will be important to remember that the success of this transformation hinges on the knowledge and skills of frontline workers at the manufacturing plants.”3
While Pharma 5.0 is in its infancy, the framework centers humans in the human–technology collaboration paradigm, a foundation essential for its success.
CDMOs and CROs Serving as Collaborative Partners to Optimizing Opportunity
Historically, leading pharmaceutical companies were vertically integrated, internally managing the entire value chain of their organizations — from discovery to commercial manufacturing. By the 1990s and early 2000s, manufacturing and much analytical work began to be seen by pharmaceutical executives as non-strategic cost and capital burdens, pressuring their organizations’ efficiency and bottom lines. However, emerging CDMO organizations, many of whom purchased manufacturing facilities being divested by large pharmaceutical organizations, were happy to provide manufacturing services and often late-stage process development support.
While innovator’s relationships with their CDMOs and CROs have been critically important for decades, until recently, the alliances were typically transactional in nature. Innovators tech transferred their developed analytical methods and drug products to CRO and CDMO organizations that, in turn, provided cost-effective capabilities and capacity.
However, the relationships between innovators and contract service organizations are now much more strategic. With the diversity and complexity of therapeutic modalities, advancements progressing at a pace never before experienced by the industry, the continually changing regulatory landscape, and the specialized skills needed, CDMOs and CROs have become, in many cases, strategic partners curating the technologies and expertise that innovators need to be agile and successful.
The industry is experiencing a “technology arms race” on multiple fronts, from technologies increasing production efficiency, like continuous manufacturing; highly sophisticated analytical technologies; and diverse capabilities and expertise supporting developing and producing novel biologics.
In many cases, it is inefficient and impractical for large pharmaceutical organizations to pivot quickly, and emerging biotechs, organizations responsible for much of the innovation, cannot afford to invest in their own facilities.
While the small molecule sector remains critical for meeting patient needs, much innovation is occurring within the biologics realm, driven by scientific advancements and greater profit potential. Nathaniel Youndt, Vice President of Business Strategy and Program Management at ReciBioPharm, illustrates the specialized capabilities and expertise today's leading CDMOs are providing supporting innovation across the industry.
“During the pandemic, the global health need allowed for rapid vaccine production with less stringent purity profiles. The focus has shifted toward higher purity standards, especially in therapeutic applications that demand smaller batch volumes but higher quality,” shared Youndt. “At ReciBioPharm, we're leveraging our expertise in design of experiments and new technologies to meet these elevated standards. We're not just producing large volumes; we're ensuring that each batch meets exacting purity profiles, which is crucial as we move beyond basic mRNA to more complex constructs like siRNA, circular RNA, and self-amplifying RNA. These new nucleic acid formats are not only more complex but also hold the potential for multivalent applications, which could revolutionize how we approach vaccines and therapeutics.”4
Increasingly Diverse Modalities Offer Promise and Challenges
As medical understandings advance and drug modality innovation progresses, researchers continue to discover new ways to create desired therapeutic or regenerative impacts. The novel modalities — gene and cell therapies, tissue-engineered medicines, antibody–drug conjugates, nucleic acid therapies, and others — advancing through the development pipeline are creating substantial opportunities for the biopharmaceutical organizations developing them and for patients with unmet medical needs.
However, these novel modalities are risky and often experience high clinical failure rates or commercial challenges due to their expense. A recently approved gene therapy treating children with metachromatic leukodystrophy (MLD), a rare nervous system disorder affecting one in every 40,000 individuals in the United States, serves as one illustration of commercial obstacles facing new modalities. The therapeutic is priced at $4.25 million and is one of many emerging therapeutics pressuring healthcare systems around the world as a consequence of being priced in the millions of dollars.5
Yet another issue is that increasing molecular diversity frequently leads to process development, control, manufacturing, and regulatory challenges. In many areas, manufacturing and analytical monitoring are struggling to keep up with the needs of these emerging modalities, which can result in longer development timelines and quality assurance challenges.
Pharmaceutical Facility Design Adopts to Meet the Needs of a Changing Industry
Three key and interrelated trends in pharmaceutical facility design are at work — the movements toward autonomous manufacturing facilities, connected plants, and facilities designed to produce personalized medicines.
Leveraging Pharm 4.0 and 5.0 frameworks, many pharmaceutical facility designers envision entire pharmaceutical production facilities run without human. Machines would autonomously run entire production processes and technologies such as robotics, advanced sensors and detection systems, data analytics, vision systems, augmented reality, virtual reality, and AI would respond to and correct manufacturing anomalies.
While completely operator-free facilities seem unlikely anytime soon, pharmaceutical organizations can and should be creating robust digital infrastructures that can connect their employees with the organizations’ operations network. This connectivity would allow pharmaceutical manufacturers to digitally distribute work across networks and factories. For example, workers at one site might require the expertise of a co-worker thousands of miles away. Augmented reality, virtual reality, digital twins, and other technologies allow workers to share knowledge and complete tasks irrespective of geographic proximity.
The commercialization of personalized medicines has generated the demand for yet another type of therapeutic production facility. While much of the pharmaceutical industry has centered around bulk drug substance and drug product plants, personalized medicine facilities must produce thousands of small-scale batches per year.
According to ISPE, there are only a handful of personalized medicine facilities currently in operation, but many more are being designed and/or under construction.6 Design considerations for drug processing facilities traditionally prioritized the equipment to be housed. However, the design priorities of personalized medicine facilities are quite different in that scheduling, material, and personnel flow are key factors along with processing equipment that often varies in scale.
Creating the Future of Pharma, Together
So, how will the medicines of the future be made? While change is the only certain thing, strategic collaborations and their contribution to the future success of the pharmaceutical industry are equally assured.
Some of these essential exchanges will be human and AI collaborations. Although it is unlikely that AI alone will revolutionize pharma, when paired with human creativity and expertise, AI-enabled technologies can significantly speed drug discovery and development, expedite the development of robust manufacturing processes, and meaningfully advance quality control.
Other collaborations will be drug innovator and contract service organization alliances. Given the rapidly changing therapeutic modality and technology landscape, it is not efficient for large pharma organizations or possible for emerging biotechs to house all the specialized capabilities, technologies, and expertise needed to advance many of today's therapeutic assets. However, as curators of specialized technologies and expertise, contract service organizations and facility designers are invaluable partners for innovators’ success.
Because the exchange of ideas and collaboration are central to addressing the myriad opportunities central to making the medicines of the future, opportunities for the industry to gather, network, and exchange ideas are essential. INTERPHEX 2025, April 1-3, 2025 in New York City, is excited to host the conversation, How Will the Medicines of the Future be Made?
References
“Pharmaceutical Market Size to Hit Around USD 2,832.66 Bn by 2033.” Biospace. 28 March 2024 https://www.biospace.com/pharmaceutical-market-size-to-hit-around-usd-2-832-66-bn-by-2033
Sangmin Paik, Ph.D. “Enabling Digital Twins With Computational Fluid Dynamics Modeling.” Pharma’s Almanac. 14 January 2025. https://www.pharmasalmanac.com/articles/enabling-digital-twins-with-computational-fluid-dynamics-modeling
Tom Wilson. “Embracing Pharma 5.0 for a patient-centered future.” Pfizercentreone.com https://www.pfizercentreone.com/insights-resources/articles/embracing-pharma-50-patient-centered-future
Nathaniel Youndt. “A New Vision for Progressing Advanced Therapies.” Pharma’s Almanac. 25 October 2024 https://www.pharmasalmanac.com/articles/a-new-vision-for-progressing-advanced-therapies
“Kyowa Kirin's gene therapy most expensive US drug with $4.3 million price tag.” Reuters. 20 March 2024. https://www.reuters.com/business/healthcare-pharmaceuticals/kyowa-kirins-gene-therapy-most-expensive-us-drug-with-43-mln-price-tag-2024-03-20/
Sean Tully, Tom Bannon. “Front-End Design of Personalized Medicine Facilities.” Pharmaceutical Engineering. 2024 May/June https://ispe.org/pharmaceutical-engineering/may-june-2024/front-end-design-personalized-medicine-facilities