Exploring an Intelligent Drug Development Paradigm

Alexander Raths - stock.adobe.com

Drug development is a risky business. For a drug entering Phase I clinical trials, there is an estimated 10% probability of eventual FDA approval (1). At each milestone, the financial stakes increase for the next development phase: average costs are $30 million in Phase I, $70 million in Phase II, and $310 million in Phase III (2). These increasing stakes demand robust, strategic scientific and regulatory support for each transition.

Even big pharmaceutical companies (collectively, Big Pharma) have challenges in managing the end-to-end development process of new molecular entities (NMEs). For example, in 2016, Pfizer’s cumulative probability of success from start of Phase I (first-in-human [FIH] study) through approval was 4%, versus 8% for the entire industry (2). By 2020, Pfizer had revived their R&D pipeline (2) to achieve greater end-to-end success in the clinic, achieving a cumulative success of 21%, versus 11% for the industry (2). Pfizer has attributed their improvement in success rate to their increased early investments in understanding the biology of the target disease and the pharmacology of an NME, including exposure at the site of action, binding to the pharmacological target, and expression of pharmacological activity. Having a portfolio of NMEs enabled Pfizer to use this enhanced understanding to weed out failures early and take calculated risks to accelerate “winners” (2,3). Eli Lilly and Company (Lilly) (4,5) and AstraZeneca (6) have employed similar “truth-seeking” early development strategies that prune portfolios early of NMEs that are likely to fail during Phase II due to lack of efficacy. Lilly claims similar success for its autonomous Chorus early-stage drug development unit (4,5). AstraZeneca has published their framework of determinants for project success and for effective decision-making: right target, right patient, right tissue, right commercial potential, and right culture (6).

In contrast, the business model for most small pharma—include emerging, virtual, and small biotechnology companies—is different than those of Big Pharma and frequently anticipate investment tranches upon achievement of certain developmental milestones, such as opening an investigational new drug (IND) application, initiation of the FIH study, or the completion of a Phase II proof-of-concept (POC) study. Frequently, the achievement of the next value inflection point for development milestones results in activity for executing a strategic plan to attempt to sell and/or license the asset, make a public offering, or take on a partnership arrangement that can enable product commercialization. Reaching these milestones for the one (or few) small pharma-owned assets is sometimes at odds with the type of “truth-seeking” early development strategies that have allowed Big Pharma’s improved odds of success at the portfolio level.

This paper describes an intelligent drug development paradigm that enables small pharma to implement a truth-seeking early development approach such as those used by progressive Big Pharma companies, aimed at efficiently maximizing the value of information needed to inform key milestone decision points and optimize the probability of success.

The tasks of drug development

All pharma developers face challenges in early clinical development (Phase I and Phase II) associated with drug substance manufacture, drug product formulation and manufacture, and anticipating the doses needed for clinical trials. These challenges arise from a lack of communication of and adherence to a common overall drug development strategy, generally as defined in the clinical development plan (CDP) to address the target product profile (TPP) across the siloed disciplines.

Historically, Big Pharma companies established standard operating procedures and ways of working within and across siloed disciplines, approaching drug development largely sequentially, handing an NME off from one siloed discipline to the next, with collaboration occurring at the end of each task. Big Pharma companies run programs in-house, and/or contract with contract development and manufacturing organizations (CDMOs) and clinical research organizations (CROs) for development services, and they have in-house teams with diverse expertise who build a robust early development strategy to accelerate entry into the clinic and keep the development program on track (4).

In contrast, today’s small pharma companies often have deep expertise in narrow areas, but they may lack internal expertise, infrastructure, and operating procedures to conduct many core drug development activities in-house, necessitating engagement of external vendors such as CDMOs, CROs, and consultants (7). This multi-vendor outsourcing approach often leads to fragmented operational challenges, loss of continuity, and failure to maximize information at each stage of development. In most cases in small pharma, the CDMO vendor is not responsible for creating the overall development strategy. Small pharma sponsors are often ill-equipped to define this strategy and yet are responsible for choosing the strengths/doses to manufacture, bearing the risk if development fails due to improper dose or formulation selection.

Further complicating this stage of development, the manufacturing of drug substance and drug product often occur in separate locations and on highly variable timelines. Drug substance and drug product manufacturing vendors have no incentive to align their schedules, leading to schedule adjustment at the Phase I clinic if drug product delivery is delayed.

With far fewer resources than Big Pharma, small pharma sponsors often feel pressure to minimize expenditures by limiting the scope of chemistry, manufacturing, and controls (CMC), nonclinical, and activities preparatory to start of an FIH or other Phase I study until the next investment tranche. Speed-to-clinic feels critical because a small pharma sponsor’s next round of funding may be tied to an upcoming development milestone, such as enrollment of the first subject in an FIH trial. The primary objectives of FIH clinical studies are to assess the safety, tolerability, and pharmacokinetic (PK) behavior of a compound, but due to financial and time pressures, sponsors may delay some critical tests until later POC studies. This rush through Phase I is often at the expense of gathering critical data that would lead to stronger Phase II trials with better chance of achieving POC and a higher probability of eventual marketing approval.

More than a decade ago, CDMOs aimed to address these inefficiencies by creating end-to-end service networks, promising efficiency to deliver cost and time savings to sponsors (8). These networks delivered compressed timelines but brought on new challenges because sites within the network communicated and collaborated poorly. Today’s CDMO networks typically market the speed of their integrated offerings to deliver drug product to the clinic but fail to address the core challenge of choosing which doses or formulations the sponsor should manufacture.

A few CMDOs have also combined manufacturing to provide small-scale good manufacturing practice (GMP) batches of drug product (9) with clinical trial services to eliminate some time gaps between findings in the clinic and adjustment of dose at the manufacturing and drug product finishing sites. This “mini-GMP” setting enables iterative manufacture and clinical testing that is faster than the traditional GMP “make and ship-to-clinic” approach and may yield a more optimized formulation.

The intelligent drug development paradigm for small pharma

Small pharma sponsors frequently hire one or more independent consultants across a variety of disciplines to coordinate the early interactive phase between manufacturing and early clinical development. Such consultants play a vital role by providing nonclinical, manufacturing, regulatory, clinical, and technical support, often acting as liaisons between sponsors and vendors. However, when consultants operate from within their individual areas of expertise strategic value can be lost, mirroring the siloed model of Big Pharma approaches that increases development risk. In addition, the task of managing multiple independent consultants across disciplines is often challenging for a small pharma sponsor.

Instead of that fragmented approach, many of the challenges of typical small pharma development can be addressed by an intelligent drug development paradigm that is functionally integrated, dynamic, parallel, and iterative. Such a paradigm is like the paradigm followed by progressive Big Pharma companies such as Pfizer (2,3), Eli Lilly (4,5), and AstraZeneca (6).

A resource-constrained small pharma stands to derive great benefit through contracting with an integrated strategic team comprised of scientific experts across core disciplines, including clinical science, regulatory, CMC, biopharmaceutics, pharmacology, and toxicology, and operating under a unified goal with the sponsor to get an asset into the clinic, successfully through Phase I and beyond. This core team serves as thought partners with the sponsor’s internal experts on scientific and regulatory matters in an on-demand manner. The strategic team works with the sponsor to define the near- to long-term objectives, and then builds a strategic clinical plan to strengthen the information available to inform key milestone development decisions. In this intelligent drug development approach, the joint sponsor/vendor strategic team’s development plan covers scenarios and contingencies that make it possible to adjust strategies and tactics based on emerging data in CMC, non-clinical, and clinical spaces. With a comprehensive and adaptive clinical plan supported by evolving, phase-appropriate CMC resources, the development program runs more efficiently and on a more predictable timeline. The evolving CMC needs are supported in parallel by one or more vendors that are qualified and directed by the strategic team. This new service model is designed with small pharma companies in mind, getting faster and more intelligently into POC clinical trials with robust data support at each milestone transition. Table I illustrates how the same level of expertise possessed by a Big Pharma entity could be deployed for resource-constrained sponsors, with examples shown for two consecutive phases of development: the first for progressing a compound from discovery into clinical development and the second for transitioning from Phase I into Phase II POC studies.

Table I. Planning and oversight activities of a strategic consulting team at two consecutive phases of drug development. IND is investigational new drug. POC is proof-of-concept.

In the intelligent drug development paradigm, the focus of Phases I and II is to achieve POC as efficiently as possible, completing all learning required to plan an efficient and complete Phase III program. Efficiency may mean parallel development of validated outcome and biomarker assessments while Phase I studies are in progress (or even before), so that they can be incorporated into Phase II studies. Efficiency may sometimes mean careful analysis of Phase I results to confirm a decision to advance the drug candidate to Phase II or Phase III.

The technical and financial failure risks of drug development add significant pressure to small, rapidly developing sponsors, making the POC a critical milestone in their business models. In many cases, partnering or selling the asset after POC is critical to carrying an asset toward commercialization. To realize these ends, small pharma sponsors need reliable and efficient execution of POC trials with deliberate speed to develop a robust data package that makes the asset attractive to potential buyers or partners. In this new intelligent clinical development paradigm, the strategic team also oversees the development of the due diligence data package, ensuring it includes all relevant efficacy, safety, and CMC data.

Moving ahead confidently

Around 2005, Lilly established Chorus, a small, operationally independent clinical development organization within the company that has specialized in drug development from candidate selection to POC (5). “The mission of Chorus is to achieve [POC] rapidly and at a low cost while positioning successful projects for ‘pharma-quality’ late-stage development. Chorus uses a small internal staff of experienced drug developers and a network of external vendors to design and implement CMC processes, preclinical toxicology and biology, and Phase I/II clinical trials” (5). “Since it was established, Chorus has demonstrated substantial productivity improvements in both time and cost compared to traditional pharmaceutical research and development” (5).

The intelligent drug development paradigm provides small pharma with access to an aligned and integrated multi-disciplinary team that builds and drives a strategic plan as seen in leading Big Pharma drug development. Aligned with a sponsor’s clinical and business objectives, the strategic team ensures maximum flexibility, coordination, and speed for efficiently executed Phase I and II studies, supported by robust preparatory nonclinical and CMC work. The team coordinates partners from the fragmented vendor space and directs activities to enhance the scientific knowledge by maximizing interaction and rapid iterative cycling across disciplines, more efficiently using resources. The resulting robust and more complete datasets across disciplines facilitate better go/no-go decisions at development milestones that are value inflection points.

References

1. Takebe, T.; Imai, R.; Ono. S. The Current Status of Drug Discovery and Development as Originated in United States Academia: The Influence of Industrial and Academic Collaboration on Drug Discovery and Development. Clin Transl Sci. 2018, 11 (6), 597–606. DOI: 10.1111/cts.12577
2. Fernando, K.; Menon, S.; Jansen, K.; et al. Achieving End-to-End Success in the Clinic: Pfizer’s Learnings on R&D Productivity. Drug Discovery Today 2022, 27 (3), 697–704. DOI: 10.1016/j.drudis.2021.12.0101/cts.12577
3. Wu, S. S.; Fernando, K.; Allerton, C.; et al. Reviving an R&D Pipeline: A Step Change in the Phase II Success Rate. Drug Discovery Today 2021, 26 (2), 308–314. DOI: 10.1016/j.drudis.2020.10.019
4. Bonabeau, E.; Bodick, N.; Armstrong, R. W. A More Rational Approach to New-Product Development. Harvard Business Review March 2008, 96–102.
5. Owens, P. K.; Raddad, E.; Miller, J. W.; et al. A Decade of Innovation in Pharmaceutical R&D: The Chorus Model. Nat Rev Drug Discov. 2015, 14 (1),17–28. DOI: 10.1038/nrd4497
6. Cook, D.; Brown, D.; Alexander, R.; et al. Lessons Learned from the Fate of Astrazeneca’s Drug Pipeline: A Five-Dimensional Framework. Nat Rev Drug Discov. 2014, 13 (6), 419–431. DOI: 10.1038/nrd4309
7. Nayler, S.; Pritchard, K. The Reality of Virtual Pharmaceutical Companies. Drug Discovery World Summer 2019, 8–15.
8. DiMasi, J. A.; Smith, Z.; Getz, K. A. Assessing the Financial Benefits of Faster Development Times: The Case of Single-Source Versus Multi-Vendor Outsourced Biopharmaceutical Manufacturing. Clin. Ther. 2018, 40 (6), 963–942. DOI: 10.1016/j.clinthera.2018.04.011
9. DiMasi, J. A.; Wilkinson, M. The Financial Benefits of Faster Development Times: Integrated Formulation Development, Real-Time Manufacturing, and Clinical Testing. Ther Innov Regul Sci. 2020, 54 (6), 1453–1460. DOI: 10.1007/s43441-020-00172-w.

About the authors

Kevin M. Kane, PhD, is CMC strategy director; Eugene J. McNally, PhD, is vice-president, early engagement and regulatory strategy; Jeff L. Garwin, PhD, MD, is associate clinical science director; and Debra A. Schaumberg is vice-president and global head; all at Strategic Development Consulting, PPD, part of Thermo Fisher Scientific.