Category: Thought Leadership

By Laura Farmer, Founder and President, Opus Strategy

The pharmaceutical industry is at a pivotal moment. Amid unsustainable cost pressures and growing macroeconomic uncertainty, AI and digital health are shifting from experimental tools to enterprise-wide drivers of change. No longer confined to pilots or innovation labs, these technologies are now reshaping how pharmaceutical companies operate across the value chain: transforming commercial engagement, enabling personalized medicine, streamlining workflows, and accelerating evidence generation. The opportunity is enormous. However, realizing its full potential requires more than adopting new tech. It demands a clear strategy, cross-functional alignment, change management, and the discipline to turn digital investments into measurable patient and business impact.

Precision Medicine

Advances in genomics, biomarkers, computational biology, AI, and real-world data are transforming personalized medicine. AI is unlocking deeper insights into human biology, revealing disease subtypes, guiding diagnostics, predicting response, and optimizing dosing so that therapies fit each patient’s biology and deliver better efficacy, tolerability and safety.  

Precision medicine is no longer aspirational — guiding diagnostics it is becoming operational. It is shaping how drugs are developed, which assets to move into later phase trials, and how treatment is delivered at the point-of-care. This evolution demands a strategic rethink: how clinical programs are designed, which biomarkers to prioritize, how novel biomarkers inform pipeline decisions, and how commercial requirements like diagnostic accuracy and clinical workflow integration must be considered early. Companies that integrate AI-driven insights into early R&D position themselves to unlock faster, more effective clinical development and better treatments for improved patient outcomes (1,2).

AI for Commercial Teams

Generative and agentic AI are revolutionizing how biopharma engages physicians, patients, and other key stakeholders. What began as digital content optimization is now evolving into intelligent orchestration, driven by generative and predictive AI that can tailor messaging, optimize timing, and inform channel strategy in real time.

By seamlessly integrating with CRM systems, field force tools, and marketing automation platforms, AI enables a unified intelligence layer that delivers hyper-personalized content and adaptive engagement strategies across the digital, in-person, and patient support channels.This goes beyond efficiency:  it’s about agility, relevance, and the ability to act on insights faster than the competition.

For commercial teams, success will increasingly depend on the ability to translate complex scientific and clinical data into actionable, customer-centric narratives at scale. AI doesn’t just automate workflows like MLR review, it amplifies reach, precision, and impact of commercial efforts in a rapidly evolving and competitive market (3,4).

Direct-to-Patient (DTP) Platforms

Direct-to-patient platforms are redefining how patients discover, access, and stay on therapy, enabling biopharma companies to bypass traditional gatekeepers and engage patients directly. Through telehealth partnerships, fulfillment, digital patient support services, and app-based adherence support, these platforms offer an end-to-end experience that biopharma can shape to improve access, adherence, and outcomes for patients.

Beyond convenience, DTP models offer something far more strategic: greater control over patient engagement, data collection, and brand experience. By reducing reliance on intermediaries like pharmacy benefit managers and retail pharmacies, biopharma gains earlier touchpoints with patients and the ability to personalize interventions, and capture real-world insights.

To capitalize on this shift, biopharma must rethink traditional access strategies and forge new partnerships with digital health platforms, retail disruptors, and tech providers. The goal: meet patients where they are while maintaining regulatory, clinical, and data integrity (5,6).

Automation and Workflow Efficiency

AI and automation are easing operational bottlenecks across the biopharma value chain—from regulatory submissions and SOP management to pharmacovigilance, quality documentation and literature reviews. These tools don’t just speed things up, they reduce risk, improve consistency, lower costs, and unlock capacity at scale.

More strategically, automation frees teams to shift their focus from operational tasks to scientific innovation and strategy. In an industry where time-to-market defines competitive advantage, intelligent automation is no longer optional or  a nice-to-have, it is a strategic imperative (7,8).

Evidence Generation and Clinical Trial Optimization

AI and data  platforms are reshaping how clinical evidence is generated, analyzed, and applied. These tools are accelerating the identification of enriched biomarkers, optimizing inclusion/exclusion criteria, supporting dynamic trial design based on real-world data, and supporting the validation of surrogate endpoints for regulatory and payer use. Evidence synthesis, historically manual and fragmented, is becoming increasingly automated, dramatically reducing development timelines and costs.

For medical affairs and clinical teams, this translates into faster insights, smarter trial design, and strong narratives to support regulatory and payer decisions. Companies that embed these capabilities into their R&D and medical affairs strategies stand to lead not only in speed, but also in scientific credibility and commercial readiness (9,10).

What Success Requires

The promise of digital transformation is real, but execution remains uneven. Many organizations face what I call “prioritization paralysis”— the inability to decide which technologies deserve scarce capital and leadership attention. Too often, companies chase trends without completing robust ROI evaluation or building a strong business case.

Digital transformation is not a checklist; it is a disciplined strategy. Leaders must separate hype from impact, align across R&D, commercial, and medical functions, and focus on initiatives that deliver measurable patient and business value (11,12).

Partnering for Impact

At Opus Strategy, we help pharmaceutical and biotech leaders bridge the gap between innovation and execution. Our team brings deep expertise across biopharma, digital health, MedTech and AI to help clients identify the right opportunities, validate ROI, and prove the value of their investments. We know how to separate hype from impact, and we focus on solutions that deliver measurable business results while advancing patient care.

Biopharma is indeed at a digital inflection point. Companies that lean in thoughtfully and embrace these technologies as strategic imperatives — rather than experimental side projects — will define the next era of medicine. The future is not merely about adopting technology; it is about creating transformation that improves outcomes, strengthens connections, and drives sustainable growth.

References

1. Deloitte. AI in pharma and life sciences. Deloitte. https://www.deloitte.com/us/en/Industries/life-sciences-health-care/articles/ai-in-pharma-and-life-sciences.html

2. McKinsey. Generative AI in the pharmaceutical industry: Moving from hype to reality. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/generative-ai-in-the-pharmaceutical-industry-moving-from-hype-to-reality

3. Deloitte. Future of pharma field force: AI-driven agility. Deloitte. https://www.deloitte.com/us/en/Industries/life-sciences-health-care/articles/future-pharma-field-force-ai-agility.html

4. McKinsey. Early adoption of generative AI in commercial life sciences. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/early-adoption-of-generative-ai-in-commercial-life-sciences

5. Deloitte. Future of artificial intelligence in health care. Deloitte. https://www.deloitte.com/us/en/Industries/life-sciences-health-care/articles/future-of-artificial-intelligence-in-health-care.html

6. arXiv. The digital transformation in health: How AI can improve the performance of health systems. arXiv. https://arxiv.org/abs/2409.16098

7. McKinsey. Gen AI: A game changer for biopharma operations. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/gen-ai-a-game-changer-for-biopharma-operations

8. Deloitte. The convergence of AI technologies and human expertise in pharma R&D. Deloitte. https://www.deloitte.com/uk/en/Industries/life-sciences-health-care/research/the-convergence-of-ai-technologies-and-human-expertise-in-pharma-r-and-d.html

9. McKinsey. Accelerating clinical trials to improve biopharma R&D productivity. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/accelerating-clinical-trials-to-improve-biopharma-r-and-d-productivity

10. McKinsey. A vision for medical affairs 2030: Five priorities for patient impact. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/a-vision-for-medical-affairs-2030-five-priorities-for-patient-impact

11. McKinsey. Scaling gen AI in the life sciences industry. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/our-insights/scaling-gen-ai-in-the-life-sciences-industry12. Deloitte. Realizing the value of artificial intelligence in life sciences. Deloitte. https://www.deloitte.com/us/en/Industries/life-sciences-health-care/articles/value-of-genai-in-pharma.html

On April 15, I had the privilege of attending the AI Healthcare Leadership Summit, an invite-only event hosted by Bessemer Venture Partners, Bain & Company, and Amazon Web Services. This summit convened many of the industry’s leading minds — CEOs, founders, clinicians, investors, and technologists — who are actively shaping the trajectory of artificial intelligence in life sciences, clinical medicine, and healthcare financing. One of the most valuable components of the summit was the unveiling of the Healthcare AI Adoption Index, a data-rich analysis of how more than 400 healthcare organizations are approaching AI adoption. The findings reflect what many of us are seeing firsthand: AI adoption is not only accelerating, it’s becoming central to enterprise strategy.

As the founder of Opus Strategy, a firm that works with investors and large companies in the pharma industry, this event offered essential insights into how AI is evolving, particularly in the life sciences, and what healthcare leaders and innovators must prioritize to stay ahead.

AI Applications in Life Sciences

Only 15% of current AI projects are categorized as vertical applications, a fact that leaves immense whitespace for startups and healthcare innovators to co-create tools tailored for a range of healthcare applications.

Within pharma specifically, AI is being utilized in preclinical applications such as molecule identification and indication selection, along with clinical applications like protocol design and even New Drug Application (NDA) submission. The technology also is being leveraged in pharma for marketing and sales.

Despite the current and potential applications for AI, trust in the technology is not quite robust. And trust will be paramount to capitalizing on AI’s potential. Additionally, outcomes continue to drive procurement decisions, creating fertile ground for strategic partnerships built on transparency, data ownership, and performance.

AI Co-Development within the Pharma Industry

While much of the early focus on healthcare AI revolved around startups, what’s emerging now is a more complex and collaborative model. Many of the most promising AI applications are being developed not just by health tech startups, but are being co-developed by internal provider teams working closely with large technology firms and cloud providers.

According to the report released by Bessemer, 57% of pharma executives believe AI will help drive new therapies over the next decade. With security concerns, costly integrations, and the need for AI-ready data (especially in pharma), executives do believe collaboration will be key. Indeed, many believe adoption risk is mitigated when collaboration exists between traditional industry players and innovators. This opinion underscores a key strategic shift: AI is no longer seen as a siloed. It’s now deeply embedded in core corporate strategy.

Despite this momentum, adoption remains somewhat limited. Only about 30% of AI pilots make it beyond the proof-of-concept stage, and within pharma specifically, fewer than 24% of innovators have reached that milestone. This lag, especially when compared to adoption rates in the payer and provider sectors, highlights the urgent need for a more agile, “test and learn” approach to drive real-world implementation.

AI Budgets and IT Spend

The Bessemer report demonstrates AI has moved beyond the experimental phase. It is now a core element of competitive healthcare strategy with 60% of healthcare executives allocating more resources to AI than to traditional IT at a time when budget authority is increasingly consolidated at the C-Suite level.

This shift marks a broader institutional commitment: 65% of AI initiatives are now funded through centralized corporate budgets, while the remaining 35% are supported at the departmental level. In the past, IT budgets were the primary obstacle to advancing AI. Now that’s not the case. Most respondents to the Bessemer survey indicated budget constraints are no longer a primary obstacle to scaling AI from pilot to production, signaling a shared understanding that AI adoption is a strategic imperative, not a discretionary expense.

That said, executives do have a preference with whom they work.

While big tech companies are often seen as leaders in generative AI, nearly half (48%) of executives say they prefer to partner with startups, especially those that bring flexibility and a collaborative mindset. Moreover, 64% of executives are open to co-developing AI solutions with early-stage companies, particularly when those partnerships offer clear, measurable value and demonstrate alignment with clinical or operational needs.

Once again, being open to collaboration is key.

Pioneers Shaping the Future

Throughout the summit, participants heard from pioneers who are already shaping this future, including former FDA deputy commissioner Janet Woodcock. The message was consistent: success in healthcare AI will be defined not only by technical sophistication, but by deep integration and collaboration, shared accountability, and measurable value.

What excites me most is the collective momentum. Healthcare organizations are no longer asking if AI should be adopted — they’re defining how it can be implemented responsibly, efficiently, and equitably. As someone who works closely with clients on strategy, market insights, and innovation in the life sciences industry, this summit reaffirmed the importance of staying informed and being engaged within the ecosystem. We need to work collaboratively to turn promise into progress.

I’m grateful to the organizers for creating such an insightful and inspiring environment, and I look forward to continuing this important work with many of the brilliant minds I met last week.

For those interested, the full Healthcare AI Adoption Index is well worth the read: https://www.bvp.com/atlas/the-healthcare-ai-adoption-index

The 2025 American Society of Clinical Oncology (ASCO) Annual Meeting held in Chicago brought together some of the world’s top researchers, pharmaceutical innovators, and clinical leaders to share groundbreaking data that could reshape the future of cancer care. From advances in real-world evidence to precision medicine breakthroughs, this year’s meeting emphasized one core idea: the future of oncology is here, and it’s increasingly personal, data-driven, and responsive to patient needs. Here are some of our takeaways:

1. Circulating Tumor DNA (ctDNA) is Reshaping Early Detection and Monitoring

One of the most talked-about topics at ASCO 2025 was the role of circulating tumor DNA (ctDNA) in oncology. ctDNA tests, often performed through a liquid biopsy, can detect fragments of tumor DNA in the bloodstream, offering early insights into cancer progression or recurrence. These tests can signal the likelihood of cancer returning months before it appears on CT or MRI scans and can help clinicians determine how well a therapy is working. At ASCO, dozens of abstracts explored ctDNA’s role in guiding treatment decisions and monitoring disease. Many focused on the use of ctDNA in breast cancer treatment. This technology continues to gain traction due to its non-invasive nature, ability to personalize treatment, and potential to identify relapse before symptoms emerge. While adoption has been swift in some areas, many oncologists emphasized the need for more real-world evidence and standardization to integrate ctDNA testing into routine care.

2. A New Standard of Care for Gastric Cancer May Be Emerging

AstraZeneca presented powerful new data from its MATTERHORN study on gastric and gastroesophageal junction (G/GEJ) cancer. Historically, fewer than half of patients with resectable gastric cancer survive beyond five years, even with perioperative chemotherapy. The MATTERHORN phase 3 trial showed that adding durvalumab—an immunotherapy drug—to the FLOT chemotherapy regimen significantly improved event-free survival compared to FLOT alone. All patient subgroups benefited from this combination therapy, with response rates and overall survival trends favoring the addition of durvalumab. Perioperative administration demonstrated improved outcomes over post-operative adjuvant treatment alone. These results position this immunotherapy combo as a potential new standard of care in a high-risk cancer type that has seen few major breakthroughs in recent years.

3. Precision Medicine is Gaining Ground in Breast Cancer

In the field of breast cancer, AstraZeneca’s SERENA-6 trial drew attention for its innovative use of biomarker-driven decision-making. The trial focused on patients with hormone receptor-positive (HR+), HER2-negative advanced breast cancer who developed ESR1 mutations during first-line therapy. The study showed that patients who switched early to camizestrant, a next-generation oral SERD (selective estrogen receptor degrader), saw median progression-free survival extend to 16 months, compared to 9.2 months for those who remained on aromatase inhibitors. This represented a 56% reduction in the risk of disease progression or death. While camizestrant is not yet FDA-approved, this data strongly supports its future role as a first-line option in patients showing early signs of resistance to endocrine therapy. These results underscore how timely identification of molecular changes can meaningfully improve patient outcomes. It was also notable that patients showed quality of life improvement, not just maintenance, during treatment.

4. Enhertu Could Dramatically Expand Breast Cancer Treatment Options

AstraZeneca and Daiichi Sankyo also shared data from the DESTINY-Breast06 trial, which evaluated Enhertu (trastuzumab deruxtecan) in patients with hormone receptor-positive, HER2-low metastatic breast cancer after endocrine therapy. The results were impressive: Enhertu delayed disease progression by over five months compared to chemotherapy, with a median progression-free survival of 13.2 months vs. 8.1 months. This translated to a 38% reduction in the risk of disease progression or death. Enhertu also showed promise in patients with HER2-ultralow expression, previously thought ineligible for targeted HER2 therapy. While not statistically significant, the finding suggests a new frontier in HER2-targeted treatment could be on the horizon. If Enhertu is approved for both HER2-low and ultralow populations, it could become an option for up to 80% of women with metastatic breast cancer, dramatically broadening its clinical impact.

5. Real-World Evidence is Shaping Cancer Research and Strategy

Beyond traditional clinical trials, real-world data (RWD) and real-world evidence (RWE) played a significant role in this year’s discussions. Companies like Flatiron Health and leaders such as Amy Abernethy are pioneering ways to generate meaningful insights from electronic health records and genomic databases. These efforts aim to support decision-making in real-world clinical settings where randomized controlled trials may not be feasible. While RWE is more scalable and can accelerate understanding of treatment efficacy, it does come with limitations—such as slower timelines and challenges in standardization. Still, as precision medicine continues to evolve, RWE is becoming an increasingly important tool in closing evidence gaps and supporting regulatory submissions.

6. The Innovation is Promising, but Adoption Lags

Despite the encouraging science, speakers and attendees alike acknowledged the reality: adoption of these new tools and treatments often lags. Whether it’s due to reimbursement challenges, lack of familiarity, or infrastructural barriers, integrating innovations like ctDNA testing or new therapies into community oncology practice is not immediate. This adoption gap can delay patient access to life-saving treatments and emphasizes the ongoing need for education, advocacy, and implementation support.

7. Funding and Trial Design Challenges Remain

While scientific momentum was evident, several researchers voiced concern about the difficulty of designing trials in a world of increasingly narrow patient subgroups. As cancer therapies become more targeted, it becomes harder to enroll sufficient numbers of eligible participants. With recent cuts to NIH funding, researchers are bracing for longer timelines and higher costs. These financial and operational pressures could slow down the speed of discovery unless strategic partnerships and novel funding models step in.

Compared to earlier conferences this year, sentiment among oncologists and biopharma professionals at ASCO 2025 seemed more optimistic, but still cautious. While innovation is progressing at a rapid pace, the practicalities of delivering that innovation equitably and affordably remain a significant hurdle.

At Opus Strategy, we understand that staying ahead of these developments isn’t just about reading the latest studies—it’s about translating them into actionable strategy. We partner with biopharmaceutical and life sciences companies to help them interpret evolving market landscapes, assess their competition, and optimize their market positioning. Whether it’s through evaluating real-world evidence, pressure-testing development hurdles, benchmarking global epidemiology data or conducting opportunity assessments, our team ensures you don’t just hear about the future of oncology—you’re ready for it.

For more insights, reach out to the team at Opus Strategy and learn how we can help you chart your course through oncology’s next frontier.

The 2025 AACR Annual Meeting delivered several notable developments in precision oncology and immunotherapy.

Much of the attention centered on non-small cell lung cancer (NSCLC) and mismatch repair-deficient (MMRd) tumors, reflecting a clear shift toward biomarker-driven treatment and earlier intervention.

For biopharma teams involved in early-stage development, lifecycle planning, or competitive positioning, these findings are especially relevant.

Opus Strategy attended AACR in San Diego to analyze key readouts, speak with cross-functional leaders, and assess what matters most for strategic decision-makers.

Below are five takeaways we believe should be top-of-mind.

1. KRAS G12D: From Undruggable to Viable

Long considered one of the most difficult oncology targets, KRAS G12D now has its first clinical validation.

RMC-9805 (zoldornasib) produced a 61% overall response rate and 89% disease control rate in previously treated NSCLC patients with this mutation. The drug showed encouraging tolerability and clear on-target activity.

This opens the door to expansion into other G12D-mutant tumors such as pancreatic and colorectal cancers. As the KRAS space becomes more defined by submutation, teams will need to rethink trial segmentation, portfolio prioritization, and positioning against other KRAS-directed therapies.

KRAS G12C inhibitors like sotorasib and adagrasib have reached the market, but G12D has remained elusive due to structural features that limit drug binding.

Zoldornasib represents a new class of KRAS inhibitors that may overcome those barriers through allele-specific targeting, creating new competitive dynamics across multiple tumor types.

2. EGFR-Mutant NSCLC: Combination Therapy Takes the Lead

The AENEAS-2 trial presented new data on combining aumolertinib—a third-generation EGFR TKI—with chemotherapy in first-line EGFR-mutant NSCLC.

The combination extended median progression-free survival (PFS) to 28.9 months, compared to 18.9 months with TKI alone. Overall survival data remains immature, but the early trend is favorable.

This raises important questions for clinical teams that have traditionally focused on monotherapy strategies. Combination regimens may recalibrate expectations around first-line durability and resistance management.

Although osimertinib remains the standard of care globally, regional access and pricing differences influence treatment decisions. Aumolertinib, already approved in China, has the potential for broader adoption if confirmatory data holds up internationally.

3. HER2-Mutant NSCLC: Zongertinib Emerges as a Contender

The targeted HER2 inhibitor Zongertinib showed promising early data in HER2-mutant NSCLC. The drug demonstrated antitumor activity and a favorable safety and tolerability profile in this genetically defined subgroup.

Although HER2-mutant NSCLC is a relatively small population, it is increasingly seen as an actionable target beyond breast and gastric cancers. Development programs already active in HER2 may now consider NSCLC as a logical extension.

Trastuzumab deruxtecan (T-DXd) is already approved for this indication, and while its overall safety profile has been described as manageable, interstitial lung disease (ILD) remains a key risk.

In clinical trials, ILD was found in up to 28% of patients and in rare cases can be fatal. Small molecule inhibitors like zongertinib may offer a more favorable risk profile if CNS activity is confirmed in future studies.

4. JYP0322 Shows Strong Activity and CNS Benefit

JYP0322, a novel ROS1 inhibitor, posted an 85.7% response rate in ROS1 TKI-naïve patients and 54.5% in those who had received two or more lines of systemic therapy. The drug also showed CNS activity (a key feature for patients with brain metastases) and maintained a strong tolerability profile.

With several ROS1 inhibitors on the market, CNS penetration and durability of response are critical differentiators. Agents without CNS data will face steeper challenges in both positioning and reimbursement.

Crizotinib’s limited CNS penetration has raised concerns about its suitability for long-term management. This is particularly true for patients with brain metastases, where next-generation ROS1 inhibitors show improved durability and CNS activity.

5. MMRd Tumors: Neoadjuvant Immunotherapy Resets Expectations

Neoadjuvant immunotherapy, which involves giving checkpoint inhibitors before surgery, is redefining the standard of care for mismatch repair-deficient (MMRd) tumors.

The approach gained attention following a 2022 study from Memorial Sloan Kettering (MSK), where all patients with early-stage MMRd rectal cancer achieved a complete response and were able to avoid both chemoradiation and surgery.

AACR 2025 data from an expanded cohort, now including MMRd tumors like endometrial and gastric cancers, support earlier use of checkpoint inhibitors in biomarker-selected patients.

As the data matures, clinical teams may need to reassess trial design, timing, and sequencing strategies. The conversation is shifting from whether the approach works to how early it should be introduced and in which settings surgery can be safely avoided.

Final Thoughts

AACR 2025 reinforced several trends in solid tumor oncology.

Precision targeting is progressing in rare subtypes, combination therapy is advancing in key populations, and early-line immunotherapy is prompting new standards in curative settings.

These shifts have implications for R&D strategy, lifecycle planning, and competitive positioning. For executive teams guiding oncology pipelines, agility in both development and messaging will be essential.

At Opus Strategy, we partner with clinical and commercial leaders to translate emerging data into meaningful strategy. Whether you’re preparing to expand an indication, evaluate new development pathways, or refine your go-to-market approach, we help align science with business priorities.

To explore how AACR 2025 developments may impact your pipeline or planning, reach out to Opus Strategy for a tailored discussion today.