Early Decisions That Shape Success In CNS Drug Development And Commercialization, Part 1

A conversation with Ginger Johnson, SVP, Neuroscience Lead, Lumanity

For central nervous system (CNS) innovation to matter, it has to reach the patients who need it. The pipeline has never been more promising, with scientific advances moving at pace. Yet too many therapies still struggle to translate that promise into clinical, regulatory, payer, and commercial success. The challenge is not that the science is failing but that critical value considerations are often brought in too late.

We caught up with Ginger Johnson, SVP and neuroscience lead at Lumanity, to discuss how companies can connect the science to the realities of CNS drug development earlier, from patient needs and endpoint strategy to regulatory, payer, and clinical adoption considerations, helping teams make stronger decisions before value is lost.

For companies that want to launch a CNS pipeline or work on a CNS drug, what should they know before starting? What advice do you have?

In my 25+ years working in biopharmaceutical asset development strategy and with a proven track record of driving growth, innovation, and value for clients and partners, I have seen first-hand what it takes to unlock the potential of assets in the CNS pipeline to advance medicines.

Biotech and pharmaceutical companies building or advancing a CNS pipeline need to define success early and design with real-world patient impact in mind. In CNS, a positive study is only one milestone.

In particular, I would highlight three things that matter most at the start of the process:

1. Define the patient, the setting, and what “meaningful benefit” actually means for the patient, you and your organization.

Be precise about the segment and care setting you’re building for: what benefit is meaningful in that context and what would realistically change clinical practice. Additionally, think about what is important in specific therapy areas:

• Alzheimer’s: A biomarker shift can be compelling, but it needs a believable path to cognitive benefit, functional impact, and reduced burden for patients and caregivers.
• Schizophrenia: Symptom improvement needs to translate into relapse reduction or better functioning that changes practices.
• Pain: A point change on a scale matters most when it translates into sustained functional improvement.

2. Choose a first indication you can win with (and don’t just choose the biggest market or a disease area championed by your CEO or CSO).

Take a step back when selecting the indication, because several factors will determine whether the program can succeed. I would recommend choosing an initial indication where:

• the scientific rationale and mechanism are a strong fit for the disease biology

• the benefit can be clearly demonstrated
• the clinical development path is feasible and the regulatory requirements are reasonably clear
• the diagnosis and treatment pathway is workable
• the commercial opportunity is viable enough to justify the cost and risk of development.

Many programs default to the largest or most visible indication first, but that is not always the strongest starting point. The better choice is often the indication where the scientific rationale, ability to demonstrate benefit, clinical and regulatory path, patient identification and treatment pathway, and commercial opportunity align most clearly. In some cases, that may mean starting with a narrower or genetically defined population rather than a broad, heterogeneous disease. For example, an orphan neurodegenerative indication with a strong biological link and an identifiable patient population may provide a clearer path to proof, while also creating a credible foundation for expansion into broader indications.

3. Build the evidence chain early, linking biology to real-world use.

Whereas previously it would be enough to demonstrate that a drug hits the target or moves a biomarker, that is no longer enough; it’s imperative that companies demonstrate that the biology translates into an outcome patients, clinicians, and regulators can understand. Equally important is that the therapy can realistically be diagnosed, delivered, monitored, and used in practice. In CNS, factors like testing, delivery logistics, site-of-care capacity, scheduling, and monitoring burden should be part of the development strategy, not treated as late-stage launch details.

What is the most common mistake you’ve seen with developing CNS drugs?

The most common mistake I have seen in CNS drug development is companies treating a CNS program primarily as a scientific proof-of-concept project, then only later trying to turn it into a therapy that works in real-world care. The science is obviously essential, but it needs to be connected early to the patient, the clinical setting, the endpoints, and the practical pathway to use. Otherwise, even a strong scientific rationale may struggle to translate into success in clinical trials or routine clinical practice.

This often shows up as sequential thinking: teams focus first on achieving a positive study, then later ask whether the result is meaningful to patients and clinicians, compelling to regulators, acceptable to payers, and feasible for health systems to adopt. By that point, core decisions may already be locked, including the population, endpoint hierarchy, biomarker strategy, and delivery model.

In practice, this miscalculation can look like:

• a target product profile that stays aspirational rather than decision ready
• biomarkers collected without clarity on what decision they are meant to unlock
• endpoints that are statistically positive but hard to interpret
• delivery or monitoring requirements treated as post-approval details, even though those requirements can determine whether patients ever receive the therapy.

I have also seen strong CNS programs starting with the real-world use case that prioritize asking:

• Who is the patient?
• How will they be identified?
• What benefit would matter to them and their clinician?
• What evidence would make regulators, payers, and health systems comfortable?

Unfortunately, if those questions are left too late, even exciting biology can struggle to translate into meaningful patient impact.

What have you seen successful neuroscience programs do differently in early development compared with programs that struggle later?

When it comes to successful CNS programs, the difference in early development compared to those that later struggle is their definition of precise and early success. These programs are specific about the target patient, disease stage, care setting, expected benefit, and what evidence will be needed to support the next major decision. They do not ask, “Can we show activity?” Instead, they ask, “Can we show a benefit that matters, in patients we can identify, with a therapy that can be delivered and used in practice?”

Organizations that consider the above also tend to choose the first indication thoughtfully. While it is tempting to start with the largest market, success often starts where the biology is strongest, measurement is tractable, patient identification is feasible, and the opportunity is still meaningful enough to justify investment. That “winnable” first setting becomes the platform for expansion.

Another difference is early integration of clinical, regulatory, payer, and adoption considerations. Strong programs pressure test endpoints, biomarkers, comparators, treatment burden, and site-of-care requirements before pivotal plans are locked. That does not make the program less scientific. It makes the science more likely to translate.

This plays out differently by therapy area:

• Orphan neurodegeneration: Natural history data, endpoint sensitivity, and referral networks are treated as strategic inputs.
• Psychiatry and psychedelics: Teams plan beyond symptom reduction, building a credible story on durability, functioning, and real-world treatment feasibility.
• Alzheimer’s: Teams recognize that biomarker-based development and diagnostic infrastructure need to evolve together.

Programs that struggle often have promising science, but establishing proof from the strategy, patient definition, and adoption pathway stay ambiguous for too long, making it difficult to build confidence with regulators, clinicians, and payers when it matters most.

What have you seen in the clinic with CNS drugs that would be helpful to know in the discovery and early-stage development phases?

Clinical reality is where the heterogeneity of CNS disease becomes unavoidable, and it should shape discovery and early development assumptions from the outset. Patients rarely resemble textbook disease models. Comorbidities, variable disease trajectories, differences in placebo response and adherence, caregiver support, and uneven access to specialists and diagnostics can all affect treatment response. These factors also influence which patients enroll in trials, how representative the study population is, and how confidently the results can be interpreted.

A few clinical realities are particularly important to consider early:

• In neurodegenerative diseases, disease stage can fundamentally change both the biological opportunity and the development path. Earlier intervention may be more biologically plausible because there is less irreversible neuronal damage, but early-stage patients can be difficult to identify and may progress too slowly to show meaningful change within a practical trial timeframe. Patients with more advanced disease may be easier to diagnose and may decline more rapidly, but there may be less remaining function to preserve and less potential for recovery. Teams therefore need to align the proposed mechanism, target population, study duration, and endpoints with the stage of disease in which the therapy is most likely to have an observable and meaningful effect.
• In orphan neurodegenerative diseases (for example progressive supranuclear palsy (PSP), Huntington’s disease, motor neuron disease, and Creutzfeldt-Jakob disease), small patient populations make natural history, endpoint selection, and access to specialized centers especially important. Teams need a detailed understanding of how quickly the disease progresses, how much variability exists between patients, and which measures are sensitive enough to detect change during the planned study period. An endpoint that performs well in later-stage disease may be insensitive in earlier patients, while an outcome that is clinically meaningful may change too slowly for a feasible trial. For example, PSP can progress relatively quickly, but heterogeneity in symptoms and progression can complicate endpoint selection. Specialty center networks therefore affect not only recruitment, but also consistency of diagnosis, assessments, biomarker collection, and long-term follow-up.
• In psychiatry, placebo response, site variability, adherence, and fragmented care are central study design considerations, not secondary operational issues. They can determine whether a true treatment effect is detected and whether the results can be reproduced across studies and care settings. In psychedelic programs, for example, a rapid improvement on a symptom scale may be encouraging, but it does not by itself establish the full value of the therapy. Teams also need to understand how long the benefit lasts, whether symptom improvement translates into functional recovery, and whether the treatment model is practical. This includes questions such as the duration and intensity of treatment sessions, staffing and monitoring requirements, the need for repeat dosing, and whether the therapy can be delivered consistently outside a small number of highly specialized centers.

I would say that the bottom line for early intervention teams is: design the program around real-world use case. If the future adoption depends on specialized diagnostics, complex monitoring, or a narrow referral network, these are not late-stage launch details, they are core development inputs.

Stay tuned for part 2.

About The Expert

Ginger Johnson, Ph.D., senior vice president and neuroscience lead at Lumanity, advises biopharmaceutical companies on asset, portfolio, and development strategy across neurology, psychiatry, and pain. She brings more than 25 years of experience spanning neuroscience research, biotechnology, life sciences investing, and strategic consulting. Her work focuses on connecting scientific innovation with the clinical, regulatory, payer and commercial evidence needed to translate promising CNS therapies into meaningful patient impact. Ginger has held leadership roles at the National Institute of Mental Health, Northwestern University’s Center for Biotechnology and Chase Capital Partners/CCMP.