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November 1, 2023

New: 6 essential pharmaceutical industry statistics to know in 2024

What major trends and market forces point the way to pharma’s future?
pharmaceutical industry statistics

Updated October 2023

The global pharmaceutical industry is facing a bold new AI-powered era (or at least it seems). While it’s true there’s a growing appetite for advanced technologies to streamline processes across the organization, life science companies are modernizing everything from clinical R&D to commercial product launches. Powerful big pharma is partnering with agile biotechs to introduce exciting new treatments. And there’s a strong focus on the patient voice, emphasizing putting choices into the hands of consumers. With so many forces at work, what are the essential pharmaceutical industry statistics you need to know in 2024?

In this article:

Looking for more industry-trend articles? Check out our 2023 life science industry predictions, 5 current pharma R&D trends, and top trends in the pharmaceutical industry.

Let’s dive into the year’s essential pharmaceutical industry stats.

Top pharmaceutical industry statistics

Ultimately, these numbers tell a story about the future of the pharmaceutical market. Leaders can see how the life science vertical is changing in response to everything from climate change and COVID-19 to supply chain issues and artificial intelligence. They are responding by taking steps to evolve and modernize.

Here are the most remarkable pharmaceutical industry statistics:

  1. Overall pharma spend to exceed $1 trillion by 2030
  2. On average, it takes 19 months to enroll patients in trials
  3. 30% of patients discontinue trials due to a poor non-clinical experience
  4. 61% of surveyed pharma companies have defined goals and objectives to enhance clinical trial diversity
  5. AI in drug discovery could reduce drug development timelines by two years
  6. 53% of pharma finance leaders say they’ll accelerate digital transformation

#1 – Overall pharmacy spend to top one trillion by 2030

The nature of drugs hitting the market is changing. Personalized medicine, targeted therapy, digital therapies, and other specialty treatments are increasing in approvals relative to more traditional treatments – significantly impacting the cost curve.

“Over the next decade, pharmacy is ripe to change significantly…by 2030, overall pharmacy spend will exceed $1 trillion.”

The effect of more individualized and specialty drug approvals has triggered a phenomenon called “pyramid math,” where three percent of patients drive 70% of pharmacy spend. While these speciality drugs hold a great deal of promise for patients with rare diseases, they also introduce a new type of economics into the industry, in which fewer patients are essentially funding the next generation of the pharma R&D process.

Read more: how insights management tech supports orphan drug development and a guide to trends in the orphan drug market.

#2 – On average, it takes 19 months to enroll patients in trials

Clinical trial timelines are designed to ensure that new treatments are safe and effective for patients. Therefore, it’s impossible – and not desirable – to rush them. But trial sponsors want to be efficient during the recruitment and enrollment periods, which are essential for keeping trials on track.

Approximately 85% of trials don’t begin on time due to enrollment issues. To some extent, this is dependent on the type of trial. For example, enrolling healthy participants in a trial may only take a few months. For other disease areas – rare diseases, oncology, and gastrointestinal conditions – enrollment can take years, significantly affecting trial success.

By making the clinical trial process more convenient for enrollment and participation, industry leaders can gain better research results, fewer failed trials, and more trust from physicians and patients. – Deloitte

Learn how to improve patient recruitment in clinical trials.

#3 – 30% of patients discontinue trials due to a poor non-clinical experience

Trial retention is an important element of successful trial execution. Study sponsors can suffer severe setbacks if enrollees don’t complete a trial. According to Accenture, the statistics are sobering:

  • Across more than 300,000 clinical trials, only 5-10% of eligible patients are even aware of the studies
  • 30% of patients drop out due to non-clinical issues
  • 19% of trials close or terminate early because they don’t have enough participants, causing an estimated $800 billion loss in value

What are the non-clinical issues that cause patients to discontinue trial participation? It’s important to remember that patients are regular people dealing with work, family, and possibly health issues, which may interfere with prescribed trial activities. Patients may find it difficult to travel to trial sites due to scheduling or the cost of transit. They also may be concerned about missing work or arranging childcare.

To minimize these issues for participants, trial sponsors investigate the benefits of decentralized clinical trials, including fewer barriers to participation and increased participant diversity. Many aspects of clinical trials – such as documentation and data collection – are already digitized. As more consumers prefer to manage their healthcare using online portals and apps, the demand for virtual or decentralized trials will likely increase.

Read more: learn about virtual clinical trials.

#4 – 61% of surveyed pharma companies have defined goals and objectives to enhance clinical trial diversity

When the FDA approves prescription drugs, consumers may assume clinical trials accurately represent the population they are designed to treat. However, most trials primarily enroll white male patients – while people of color make up about 39% of the population, these groups only represent between 2-16% of patients in trials.

Clinical trials primarily enroll white male patients, with consistent underrepresentation of women, the elderly, and people of color – especially Black and Hispanic patients. While people of color comprise about 39% of the US population, these groups represent 2% to 16% of trial patients. This disparity hurts patient outcomes and drug companies’ bottom lines.

Accordingly, more than half of pharma companies have identified a strategy to address this issue. Some elements of these strategies include:

  • Working with patient groups, community organizations, CROs, and other groups to establish a more sustainable trial infrastructure
  • Updated data collection to support the accumulation and sharing of demographic and real-world data
  • Developing patient-focused resources that make it easier to learn about, enroll, and participate in clinical trials

Read more: how technology is helping confront the life science diversity issue and why diversity in clinical trials is essential.

#5 – AI in drug discovery could reduce drug development timelines by two years

Artificial intelligence in drug development offers intriguing possibilities for pharma. By finding efficiencies in the drug development process, the industry could save tens of millions yearly, bring treatments to market more quickly, and ultimately improve patient outcomes.

Accordingly, the industry is increasingly relying on AI to support drug discovery. One of the most striking pharmaceutical industry statistics is that spending on AI will reach $3 billion by 2025 as companies invest in technology that may reduce the time and costs required to bring a new drug to market. AI-based drug discovery alliances are also increasing, from just 10 in 2015 to 105 in 2021.

The aim is to overcome a very low success rate in drug discovery, with just 10% of candidates making it into clinical development despite applying new computational technology techniques to handle an ever-growing amount of biomedical data. It takes 12 to 18 years and about $2.6 billion for a new drug to reach the market – even for high performers among the top 10 pharmaceutical companies.

Drug companies are also betting big on AI in clinical trials. Amgen expects AI to “shave two years off the decade or more it typically takes to develop a drug.”

Learn more about artificial intelligence in drug development.

Want to leverage AI, but don’t know where to start? Start with us.

#6 – 53% of pharma finance leaders will accelerate digital investment with analytics, AI

Last year, pharma leaders said they expected pandemic-related investments in digital transformation to continue. Looking ahead, more than half of pharma finance chiefs say they’ll accelerate digital transformation with advanced data analytics, AI, and other solutions to “drive standardization and automate as many processes in every area where it makes sense,” according to PwC research.

Although many life science companies have embarked on digital transformation initiatives, industry leaders must tune into the value these efforts deliver and whether their operations are truly transformed. PwC recommends using metrics to measure how many hours of work are being eliminated across a specific time frame, how much outcomes can be accelerated, and how much quality improvement they can achieve under a transformed digital framework.

Learn how insights management technology is solving pharma’s productivity problem and how AI moderation in pharma helps companies work more effectively.

Pharmaceutical industry statistics: main takeaways

The pharmaceutical industry is rapidly evolving to meet formidable challenges. The strategic deployment of technology – including artificial intelligence, insights management, advanced analytics, and other tools – will support pharma teams as they embrace changing times. Organizations should also continue to emphasize developing and evangelizing patient services, trial diversity, and an overall patient-centric approach.

This year’s top pharmaceutical industry statistics paint a clear picture. While drug companies will see the benefits of digital transformation in total pharmaceutical sales, the most important benefit is to patients who will receive better drugs and treatments within shorter timelines.

Deloitte. 2022 Global Life Sciences Outlook – Digitalization at scale: Delivering on the promise of science.
Cowen. Speeding Innovation: A Primer on AI in Pharma R&D.
Deloitte. Enhancing clinical trial diversity.
HBR. Addressing demographic disparities in clinical trials.
GlobalData. Artificial intelligence (AI) in drug discovery: thematic research.
Deloitte. Biopharma digital transformation: Gain an edge with leapfrog digital innovation.
OliverWyman. Pharmacy 2030: 5 Bold Predictions.–5-bold-predictions.html
Reuters. Big pharma bets on AI to speed up clinical trials.

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