Lifyorli Approved in Platinum-Resistant Ovarian Cancer Thanks to a 35% Reduction in Mortality

Lifyorli (relacorilant, Corcept Therapeutics) received its first approval on March 25th based on the results from the phase 3 ROSELLA trial, which looked at the Corcept agent as an add-on to nab-paclitaxel in platinum-resistant ovarian cancer (PROC) patients who have received prior bevacizumab. [1] These patients have limited treatment options and a mortality rate in the first year of platinum-resistant disease that is 16 times higher than that of their age-matched peers. Recent FDA approvals have emerged in subsets of PROC patients with actionable biomarkers, but little options remain for patients without them. As a result, these patients will typically receive non-platinum chemotherapy, such as paclitaxel, pegylated liposomal doxorubicin, or topotecan. [1]

When added onto nab-paclitaxel, Lifyorli offered over 4 additional months of survival compared with nab-paclitaxel alone. (16.0 vs 11.9, HR = 0.65) [1] This substantial benefit helps to meaningfully address the most substantial unmet need of this disease. However, the regimen did not offer the same magnitude of improvement in progression-free survival and overall response, only scoring one additional month of PFS (6.5 vs 5.5) and not achieving a statistically significant difference in the secondary endpoint of overall response rate (36.9% ORR vs 30.1%, p=0.17). [2] Together, these attributes make up an interesting efficacy profile, as an OS improvement more than 4x the PFS improvement of a given regimen is highly uncommon.

When taking into account the modest drawback of increased side effects, Lifyorli achieves a solid 5.8% clinical innovation when compared to nab-paclitaxel. While this is not a blockbuster score, it is no doubt a meaningful efficacy improvement that will make this drug competitive.

Figure 1: Drivers of Clinical Benefit

[1] U.S. Food and Drug Administration. FDA approves relacorilant with nab-paclitaxel for platinum-resistant epithelial ovarian, fallopian tube, or primary peritoneal cancer. Published March 25, 2026. Accessed April 7, 2026.

[2] FDA approves relacorilant plus nab-paclitaxel for platinum-resistant ovarian cancer. OncLive. March 25, 2026. Accessed April 7, 2026.

Oveporexton Could be a Game-changer for Narcolepsy Type 1

Narcolepsy is a rare neurological disorder that affects an estimated 200,000 Americans [1], and about half of those people have narcolepsy type 1 (NT1) [2]. While both NT1 and NT2 cause sleep attacks and excessive daytime sleepiness, NT1 also causes cataplexy: episodes of sudden muscle weakness often triggered by intense emotions. Not only does NT1 severely impact quality of life, but it can also be dangerous when cataplexy episodes or sleep attacks occur during activities such as driving or operating machinery [3].

In February 2026, the FDA accepted the NDA for oveporexton, Takeda’s investigational agent, and granted it Priority Review. Instead of simply managing symptoms, oveporexton is a potentially first-in-class OX2R-selective agonist that targets the orexin deficiency that causes NT1 [4].

Oveporexton yields an exceptional clinical innovation score of 20.4% over standard-of-care Xywav when it is priced at a modest premium. Based on currently available data, we view oveporexton as a more efficacious and convenient option, and, if launched at this price point, expect it will take a commanding lead of the NT1 market.

The Problem with Primary Market Research

Pharmaceutical companies spend millions on primary market research (PMR) every year — and often walk away with the wrong answer. PMR plays a genuine role in the R&D process: interviews with physicians provide insight into treatment paradigms, patient types and “journeys,” and reasonable expectations for the future of a disease. Equinox Group routinely conducts such interviews to inform our modeling efforts. This type of research has been a staple in the industry for decades, making it something people at all levels of organizations understand and can use to extract actionable insights. So, what’s the problem?

Too often, PMR is asked to be something it is not: a replacement for rigorous techniques that can quantify the advantage of a particular drug over another and communicate how that advantage actually translates to patient share potential. Below, we examine the specific instances where PMR comes up short and explain the approaches we take at Equinox Group to overcome these deficiencies.

1.      Primary market research is not dynamic

Given that PMR consists of semi-quantitative interviews, much of the content of these interviews is only applicable so long as important details such as the treatment paradigm, current clinical data, and competitive pipeline remain unchanged. For example, if new post-approval data that come out show a drug to be a much greater improvement over the standard of care than previously thought, such as in the case of Kisqali in HER2-, HR+ 1st line breast cancer, any PMR done involving the current treatment paradigm and efficacy in this population prior to the new data being read out would immediately become outdated and of little use to development teams. So, if a company wants new insights into the potential of their drug in the market, they have no choice but to commit more time and money to additional PMR.

At Equinox Group, we handle this problem by creating dynamic, data-driven models that can instantly deliver new outputs with a few clicks of a button. Any clinical data, launch date, competitor, or price of an agent can be updated in our models as soon as that new information is available, resulting in a new patient share prediction for your agent.

Consider the Kisqali example. At launch, Kisqali showed a mere 0.5% improvement over Ibrance — barely enough to move the needle — and initial sales reflected that.

Figure 1: Kisqali at launch

However, years later Ibrance was found to have disappointing survival data, proving it to have been far less efficacious than previously thought. A slight improvement in efficacy for Kisqali was also shown over this period. As a result, Kisqali actually proved to be far superior to Ibrance and that was reflected in the patient share that it ended up receiving.

Figure 2: Kisqali update

In our model, this shift was captured instantaneously by updating a handful of numbers — a process that took seconds, not months at no additional cost.

2. Primary market research is not unbiased empirical data

As noted above, PMR is effective in obtaining insights from physicians regarding a variety of topics. However, these insights remain opinions — capable of being influenced by personal biases — and do not reach the level of objectivity of empirical clinical evidence. This is especially true in longer interviews, where respondents become fatigued and the quality of their answers deteriorates. Framing effects compound this problem: the way an interview is structured can meaningfully shift the responses given. While exercises such as conjoint analysis can yield a rough estimate of how one additional month of mPFS or a cleaner side effect profile affects commercial success, this method is not optimal.

As a core principle, the qualitative should only be used to predict the qualitative, while the quantitative should predict the quantitative. Results from PMR can suggest whether a drug will obtain “significant” share and dominate the market, but they cannot reliably pinpoint what that share would be.

By looking at historical drug launches and quantifying the effect of the clinical innovation of a drug on its patient share potential, we have a way of discovering the impact of these factors on commercial outcomes strictly based on peer-reviewed clinical data without the need for any guesswork or opinion.

3. Preference share ≠ patient share

While the outcomes of conjoint analyses are not without their uses, at times they are misinterpreted. Perhaps the most important of these outcomes is preference share – an estimate of the percent of physician’s that would choose a given TPP among the profiles of all relevant drugs in the market. Assuming that the interviews are conducted in a way that minimizes bias, the insights gained regarding the relative strengths of TPPs are actually of great value. However, they cannot be used as a proxy for patient share. This is in large part due to the fact that these interviews are incapable of capturing the intricate market dynamics that contribute to a drug’s share. Furthermore, the TPPs that are being assessed lack the necessary detail and often do not consider important factors such as order of entry or price. Therefore, just because we can obtain an estimate for what percent of prescribers favor TPP A over TPP B, it does not necessarily mean that we can know what share either of these agents will obtain. It is also important to note that the subjects of these interviews are, at times, not a nationally representative sample of prescribers.

We avoid these issues by deriving our patient share projections from a consistent, analytical framework that weights clinical innovation (which includes price), order of entry, and competitive environment according to the results of our extensive work with historical drug launches.

4. Primary market research is expensive and labor intensive

Finally, PMR projects often take months and impose large costs upon biopharmaceutical companies. As mentioned above, these costs may compound as new information makes additional research necessary.

In comparison, Equinox Group’s models can be completed in as little as 6 weeks and include two years of after-sales service from the project start date. Because our models are driven by published clinical data rather than primary fieldwork, they can be updated in real time by the client as new information becomes available — without incurring additional research costs every time the market shifts.

If you’d like to see more about this framework, we’d be glad to walk you through a live example. Feel free to schedule a meeting.

Since 1995, Equinox Group has provided analytics to support R&D decisions at biopharmaceutical firms, assessing the potential of drugs from discovery to launch, and anywhere in between. Equinox Group specializes in predicting the commercial performance of drug programs in all stages of research and development, delivering quantitative insights regarding:

• Disease Area Strategy

• Business Development Decisions

• Market Access

• Patient Share Forecasting

• Epidemiology and Patient Flow

Gene Therapies for Sickle Cell Disease: Expensive but Worth It

Sickle cell disease affects roughly 100,000 Americans and is more common among African American and non-Hispanic Black people [1]. About 20,000 suffer from recurrent vaso-occlusive crises (VOCs), making them ideal candidates for the novel gene therapies Casgevy (exagamglogene autotemcel, Vertex) and Lyfgenia (lovotibeglogene autotemcel, bluebird bio, rebranded as Genetix Biotherapeutics) [2]. Priced at $2.2 million and $3.1 million, respectively, these drugs are highly innovative and – we conclude – worth the high price tags if payers can figure out how to foot the bill.

Approved in December 2023, Casgevy is a CRISPR/CAS9-based therapy, the first of its kind. Its administration procedure is similar to that of a stem cell transplant and it is incredibly efficacious, with 93% of patients in the clinical trial remaining VOC-free 12 months after treatment [3]. Casgevy also boasts an approval in transfusion-dependent beta-thalassemia, a rare blood disorder that affects only 1,300-1,500 people in the US [4]. Lyfgenia is similarly efficacious and works via a lentiviral vector to insert a functional copy of the beta globin gene to increase the production of normal hemoglobin.

Both therapies demonstrate high clinical innovation when compared to the standard of care, hydroxyrurea, with a direct cost amortized over three years. Amortization is based off clinical data demonstrating that patients who achieve VOC-free status over 12 months remain VOC-free for approximately 3 years [5, 6]. This assessment may change as more long-term data becomes available. With the life expectancy of sickle cell disease patients being far shorter than for those without the disease, these therapies have the potential to substantially close that gap, with a University of Washington study finding a benefit of approximately 17 years of increased life expectancy from the gene therapies [7]. Our model captures a dramatic 85% reduction in mortality to align with this. These therapies are even more impressive when considering the high unmet need of sickle cell disease, in addition to the societal and indirect cost savings they may bring.

However, the issue of paying for these high-priced therapies looms large. An analysis conducted by the Institute for Clinical and Economic Review (ICER) in 2023 concluded that they are cost-effective at a price range of $1.5-$2 million [8]. At $2.2 million, Casgevy is pushing that limit, and at $3.1 million, Lyfgenia is well out of the range. With these steep price tags, it will be a challenge for payers to figure out how to pay for them, especially considering that a large percentage of the patient population is underserved and on Medicaid [9]. Currently, CMS has proposed an outcomes-based pricing scheme (CGT access model) that individual states can opt into. Only patients enrolled in Medicaid could benefit from the model, which began in early 2025.

This model has the potential to reduce the cost for states to bear, as CMS is the central negotiator for all states and will be providing federal funding for the treatment. States can choose which gene therapies to cover [10]. Based on our analysis, we believe that covering Casgevy is more reasonable than Lyfgenia, but having more options could be beneficial for patients, even with Lyfgenia’s black box warning for hematologic malignancy that demands long-term monitoring indefinitely [11]. Manufacturers will be encouraged to provide rebates and reimburse accordingly in cases where clinical performance falls short. The initiative will also be collecting data over eleven years, with an outcomes-based agreement term of one to six performance years, which will provide further insight into navigating these expensive gene therapies [12]. The model does not include private insurance plans for those not enrolled in Medicaid. Patients on private insurance plans may face additional requirements for treatment, such as meeting a specific threshold of number of VOCs per year, and a baseline level of decent health.

Gene therapies have limits; they are not foolproof cures. Not all cells can uptake the edits, there may be off-target gene editing effects, they are not effective for every patient, and immune system responses may limit efficacy and compromise health [13]. The treatment journey is also time-consuming, with the Casgevy website stating that it can take up to one year [14]. Since long-term data are not currently available, we must learn as we go, but it is clear that Casgevy and Lyfgenia are an important milestone in the cell and gene therapy space.

Keytruda Grabs its 42nd Approval in PD-L1+ PROC

Keytruda (pembrolizumab, Merck) received its 42nd approval from the FDA this Tuesday, February 10th based on the results from the phase 3 KEYNOTE-B96 trial, which looked at the blockbuster PD-1 inhibitor as an add-on to paclitaxel with or without bevacizumab in PD-L1+ platinum-resistant ovarian cancer (PROC). [1] This subset of ovarian cancer patients has developed resistance to standard platinum-based regimens. As a result, they receive non-platinum chemotherapy, such as paclitaxel, pegylated liposomal doxorubicin, or topotecan.

When compared to paclitaxel +/- bevacizumab, the Keytruda regimen showed improvements in survival, progression, and response while maintaining a comparable safety and convenience profile. Importantly, the mortality benefit is what stole the show: an impressive 30% increase in mOS over paclitaxel +/- bevacizumab (19.2 months vs. 14.0 months). [2]

Taking into account the cost impact of adding on Keytruda, the Clinical Innovation is clawed back slightly to a respectable 5.0% overall (Figure 1). Although Keytruda has seen higher levels of innovation elsewhere, such as its many NSCLC indications, a score of 5% typically suggests market differentiation and shows promise for Keytruda's use in this space.

This Clinical Innovation exhibited by Keytruda will increase in the coming years, as Keytruda is scheduled to lose exclusivity in 2028, which will slightly ease the cost burden.

[1] U.S. Food and Drug Administration. FDA approves pembrolizumab with paclitaxel for platinum-resistant epithelial ovarian, fallopian tube, or primary peritoneal carcinoma. February 10, 2026. Accessed February 12, 2026.

[2] Cortese T. Pembrolizumab combo significantly improves PFS/OS in recurrent PROC. CancerNetwork. October 18, 2025. Accessed February 12, 2026.

Plan for the Best, Prepare for the Worst - Handling Uncertainty in R&D

Where the Uncertainty Lies

Assets in mid to late-stage development are seldom immune to uncertainty surrounding their efficacy and safety profiles as well as that of their competitors. When considering these variables along with launch timing and the potential for reimbursement friction, traditional techniques such as conjoint analysis are rendered ineffective. Such circumstances require far more objective, dynamic, and future-proofed approaches.

A Data-Driven Approach

Using our unmet need framework, Equinox Group consistently quantifies the clinical improvement offered by a drug using a metric that we call Clinical Innovation. This measure has proven to be highly predictive of peak-year patient share and has been the basis of our analyses for over 30 years.

By objectively quantifying the Clinical Innovation of a new drug and all of its relevant competitors, we enable our clients to prepare for all possible scenarios that they will face during development and to seamlessly toggle between them.

Wargaming with Multiple TPPs

By quantifying the uncertainty in a given indication, we can understand its implications with remarkable accuracy.

Consider, for example, a chronic disease with three agents currently in the market. Working alongside the client, we come up with a base case, an upside case, and a downside case for their new drug, taking into account efficacy, safety, side effects, dosing, administration, price, and launch timing. Under the base case, the new drug achieves 20.3% share of drug-treated patients by the end of 2031. Under the upside and downside cases, it achieves 29.3% and 14.7% respectively. As a result, in a world where no competitors are launching in the coming years, we have bounded the share potential between 14.7% and 29.3%. By assigning probabilities to each of the three scenarios, a simple weighted average will yield the expected share by the end of 2031 under the assumed conditions. In this example the modeled probabilities of the base, upside, and downside cases are 71%, 21%, and 8%. This results in an expected value of 21.7% patient-share by 2031.

Figure 1: Launching without a threat

Introducing Competitors

By studying the different scenarios in Figure 1, it is clear that the client agent has moderate potential. Now, consider a highly innovative competitor, which we call Threat 1. With Threat 1 launching one year later than the client agent, it will have considerable, yet diminished, impact on the terminal shares. Now, the client agent 10.4% patient-share in the base case and 19.0% and 6.1% in the upside and downside cases respectively.

Using the same probabilities of 71%, 21%, and 8%, we get an expected value of 11.9% patient-share by 2031. These probabilities can be informed by input of the client organization and approximated through Monte Carlo simulations, which are easily implemented into our framework when handling uncertainty around all relevant product attributes including launch timing.

Analyses like this can be made as complex as needed, allowing for up to 15 different drug profiles, characterizing the variety of potential attributes of your drug as well as all relevant competitors.

Figure 2: Launching with a threat

What About When the Data Changes?

Whether it be new clinical data pertaining to your agent or any of its competitors, the dynamic nature of these models allows client organizations to change the relevant inputs within a matter of minutes with no additional cost. That means no need for funding 50 additional interviews with leading physician’s, no need for creating new stimuli, no guesswork, and no time wasted in order to obtain new patient-share estimates. 

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Equinox Group has fine-tuned these methodologies and others over the past 30 years to help biopharmaceutical companies handle challenges in R&D. Our specialties range from disease-area strategy and market access to patient share forecasting and patient flow modeling.

To learn more about our process, click here to schedule a meeting with one of our practice leaders.

Finding the Best R&D Opportunities

R&D leaders making investment decisions must rely on opportunity assessments from program advocates. Equinox Group offers independent analyses that allow decision makers to add an objective perspective to these discussions, leading to a fact-based conversation about the clinical and commercial merit of the various projects competing for R&D resources.

“But I don’t have TPPs, what can I do?”

We spend much of our time talking with clients about how good their TPPs look and what patient shares they can expect to achieve in order to guide indication prioritization. To read a case-study on how we do this, click here.

But what can we do for you if you don’t have TPPs yet?

The answer is a two-step process, which we call Disease Area Scan. First, we characterize the unmet medical need, epidemiology, and competitive intensity in all of the populations of interest. This allows for cross-indication comparisons that help identify which opportunities offer the greatest potential for commercial success. Next, we examine each of those opportunities individually, discovering what level of improvement is required in specific product attributes in order to achieve a certain level of Clinical Innovation and peak-year patient share. These analyses are grounded in peer-reviewed literature and hard clinical data, removing subjectivity and opinions from the equation.

Step 1: Characterizing unmet medical need, epidemiology, and competitive intensity

We begin our modeling process by diving into the most recent peer-reviewed literature pertaining to each indication, quantifying the level of unmet need under the current standard of care. See Figure 1 for a detailed breakdown of what we measure.

Figure 1: Factors we assess

These measures are then mapped onto a 0 to 5 scale to produce a single “unmet need score,” with a higher score indicating a higher level of unmet medical need.

Next, we align with the client organization on the epidemiology and competitive pipelines in each indication. We represent the latter by a probability weighted score indicating the expected number of head-to-head competitors that a drug will face at launch. We call this the “competitive intensity.”

Figure 2: Competitive intensity vs. unmet medical need

Looking at Figure 2, we can identify the most attractive opportunities, which are those with sizeable populations, considerable unmet need, and relatively low competition. Granted, two questions still remain. First, how would the specific drug need to perform in these populations in order to be successful? Second, in what indications do you realistically believe that you can achieve that performance?

Step 2: Using Heat Maps

In order to answer these questions, we can turn to a series of heatmaps, which guide development teams in understanding what levels of Clinical Innovation are achieved by specific efficacy and side effect profiles. Below in Figure 3, we will explore a situation where the current standard of care is pembrolizumab with a median progression-free survival of 6.9 months. We see that an improvement of 1 month in mPFS and a similar side effect profile will result in a 4.6% Clinical Innovation, which is slightly below the recommended 5% threshold. However, if the new drug also offered a side effect profile similar to that of crizotinib, it will achieve a 5.8% Clinical Innovation and likely have a favorable commercial outlook. (For this analysis, it was assumed that an improvement of one month in mPFS also led to an improvement of two months in mOS)

Figure 3: An introduction to heat maps

By focusing on relative improvements under the Equinox framework, development teams are able to identify indications where their agent has the potential to be competitive (those where Clinical Innovation 5-10%) and those where it could be a homerun (Clinical Innovation >10%). In situations where the clinical team is not ready to commit to specific efficacy values for their TPPs, this approach allows teams to prioritize those indications where they are more confident of “getting into the green”. These heat maps can be generated for a variety of attributes, allowing for a comprehensive and thorough analysis of potential products that projects a variety of scenarios. 

What About Share Potential?

While Clinical Innovation is a powerful predictor in itself, we don’t have to stop there. Combining the clinical innovation scores of hypothetical TPPs along with the corresponding competitive environment, unmet need, and epidemiology allows for the preliminary estimation of peak-year patient share using our Disease Target Assessment (DTA) framework. Given its dynamic nature, it is easy to conduct “what if” analyses with a variety of TPPs in each indication. Additionally, once TPPs are finalized, they are easily input into the model and adapted to continue to guide the R&D process. To read more about what is behind our analysis and how it predicts share, watch this quick video.

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Equinox Group has fine-tuned these methodologies and others over the past 30 years to help biopharmaceutical companies handle challenges in R&D. Our specialties range from market access and go/no-go decisions to patient share forecasting and patient flow modeling.

To learn more about our process, click here to schedule a meeting with one of our practice leaders.

Using Equinox Drivers Charts to Understand Fabhalta's Success in PNH

Paroxysmal Nocturnal Hemoglobinuria (PNH) is rare blood disorder estimated to have a global prevalence of 12 to 13 per 1,000,000 people [1]. This condition can potentially lead to kidney disease, hemolytic anemia, and even life-threatening blood clots [2]. Until the C5-inhibitor Soliris (Alexion, eculizumab) was approved in 2007, there were no approved therapies for PNH [3].

While Soliris, along with Alexion’s other C5 inhibitor, Ultomiris (ravulizumab, which was approved for PNH in 2018 [4]), are still considered standards of care, the market has grown with the approvals of Empaveli (Apellis, pegcetacoplan), Fabhalta (Novartis, iptacopan), and PiaSky (Roche, crovalimab). Using Equinox drivers charts can help us understand how these newer entries compare to Alexion’s drugs.

Select First Drug Soliris biosim Ultomiris Empaveli Fabhalta Piasky

Select Second Drug Soliris biosim Ultomiris Empaveli Fabhalta Piasky

Select two drugs above to see the drivers chart

Equinox characterizes a drug’s improvement relative to a previous standard of care or another drug with a Clinical Innovation (CI) score, which quantifies how much the new agent lowers unmet need in the indication. For frame of reference, products with >2% CI score are typically commercially viable, products with >5% CI score are commercially successful (top 3-4 in market), and products with >10% CI score are market dominators.

Fabhalta has a whopping CI score of 29.9% when compared to Ultomiris. Though Fabhalta being the first oral agent in this indication is an improvement on its own, its substantial efficacy benefits flow through to improve morbidity and mortality across the board. Although Fabhalta has the highest WAC ((Wholesale Acquisition Cost) among the PNH drugs in this analysis, this is offset by reductions in hospitalization and associated medical costs.

While Empaveli improves upon Ultomiris’s efficacy, it does not do so to the same extent Fabhalta does. Additionally, while Empaveli can be administered at home, the frequency of administration is increased, offsetting some of its convenience benefit. In most cases, a 10.0% CI score would be expected to be a market dominator, but because it still falls far short of Fabhalta, this would be an exception.

Finally, although Piasky is more convenient than Ultomiris, this is not enough to overcome its marginally reduced efficacy at the current WAC. We do not expect it to be competitive in this market, especially against newer drugs that reduce unmet need further, such as Fabhalta and Empaveli.

Soliris 2007 reflects Soliris WAC at launch; all costs inflated to 2025 USD.

Equinox also acknowledges the approval of Voydeya in this indication, though it was not included in this analysis due to it being approved as an add-on therapy for Soliris or Ultomiris, not a monotherapy.

Measuring Risk in R&D

The Problem

It is no secret in the biopharmaceutical industry that a new drug’s clinical improvement is strongly predictive of the share of patients it achieves. Consequently, drugs that offer little clinical improvement expose developers to commercial risk.

Many organizations, while aware of this problem, continue to lack a proven methodology to identify and quantify that risk. This exposes them to the possibility of advancing undifferentiated drugs that will experience low market access and vulnerability to future competition.

The Solution

Equinox Group has quantified the relationship between clinical improvement and patient share by comparing the magnitude of improvement delivered vs. share achieved in the real world in a large set of historical drug launches. Clinical improvement reflects advances in efficacy, safety, tolerability, dosing, and patient outcomes. Our metric for clinical improvement includes all of these domains and measures the percent reduction in medical need the new drug offers relative to the standard of care. We call that measure of improvement  “Clinical Innovation”.

Measuring Clinical Innovation: A Data-Driven Approach

For 30 years, Equinox Group has used a validated, data-driven approach to measure the clinical innovation offered by new drugs across hundreds of indications. See this two-minute video explanation:

The Link to Commercial Potential

Over many years we have re-evaluated the relationship between clinical innovation and patient share; it has been remarkably stable over time. Below is a table of historical drug launches and where they score in the Equinox Group framework.

As a rule of thumb,

• High Innovation: Drugs that offer 10% or more clinical innovation nearly always dominate the branded segments of their markets.

• Medium Innovation: Drugs with 5% to 10% innovation usually compete well.

• Low Innovation: Drugs with 0-5% improvement are in a gray zone and may be seen as undifferentiated, especially by payers.

• Lack of Innovation: Drugs with negative clinical innovation nearly always get low patient shares and disappointing sales.

How Much Clinical Innovation is Enough?

The clinical attributes anticipated in early R&D programs are rarely realized by the end of development. As time goes on, assets often acquire “warts,” whether it be unexpected side effects, lower than expected efficacy, or both. Programs that start with modest clinical aspirations are likely to offer unacceptable levels of innovation at launch.  We call this phenomenon “attribute drift.”

We recommend that drug development teams aim to achieve clinical innovation of at least 5% to reduce exposure to attribute drift and the commercial risks described in the beginning of this paper. Our tools allow teams to tie the expected clinical attributes of a new drug first to its level of clinical innovation, and then to patient share to forecast revenue potential.

The Take-Home

Equinox Group’s proven method to measure clinical innovation and predict peak-year patient share for target product profiles is accurate.  It’s also less expensive, more flexible, and quicker to execute than conventional market research-based techniques.  We use this approach to inform decisions about individual programs (pipeline and BD), to help therapeutic area teams set aspirations, and to inform R&D portfolio assessments.

Who Are We?

Since 1995, Equinox Group has provided analytics to support R&D decisions at biopharmaceutical firms, assessing the potential of drugs from discovery to launch. Our validated techniques will save you time and money, as well as overcome the deficiencies of traditional market research.

We have evaluated thousands of drug profiles across hundreds of indications in oncology, immunology, rare diseases, cardio-metabolic disorders, infectious disease, neurology, pulmonology, urology, ophthalmology, and endocrine disorders. We also have tailored methods to solve the unique analytical challenges that arise in oncology and rare diseases.

Using this methodology, we have developed a suite of tools to inform whatever R&D decisions you’re facing in any stage of development, including: setting indication priorities, supporting go/no-go decisions, assessing market access and pricing potential, share forecasting, and patient flow modeling.

How Equinox Group Models Drugs in R&D: The Case of Alecensa in 1L ALK+ NSCLC

We routinely share our view of new drugs coming to the market; for instance, a few months ago, we posted an article detailing top-line results of an analysis of Enhertu in 1L HER2+ metastatic breast cancer.

This article shows in detail how Equinox arrives at a peak share estimate for a new drug treatment, using the example of alectinib (Alecensa, Roche/Genentech) in 1L ALK+ non-small cell lung cancer (NSCLC). Alecensa was approved in this indication 8 years ago; we’ll show how our methodology predicted it would achieve 60% peak share using publicly available data and our Disease Target Assessment framework.

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The Framework

Equinox Group’s Disease Target Assessment (DTA) model quantifies the level of medical need in the target population based on peer-reviewed literature. This framework characterizes the adequacy of the current and possible future standards of care (SOCs) to serve as a benchmark for evaluating client product profiles.

We start by characterizing unmet medical need within each defined patient population, quantifying unmet needs in these product attributes:

• Efficacy

• Safety/tolerability

• Dosing

• Price

as well as key elements of the burden imposed by the disease:

• Mortality

• Morbidity (pain, chronic disability, hospitalization, and HRQOL)

• Non-drug health care costs

For each domain and subdomain, we use consistent utility functions to derive a score on a 0-5 scale (with 0 representing no unmet need and 5 substantial unmet need). Each domain has a fixed weight based upon its importance, as verified through regression analysis of launched agents. The sum of the weighted scores measures the total unmet medical need for patients treated with the profiled therapy.

Through validation against actual market performance, Equinox has demonstrated that the Clinical Innovation of a new drug (or regimen) offers reliable insight into its ability to compete. A few rules of thumb hold up surprisingly well in projecting a new drug’s commercial outlook:

• Drugs with 10%+ Clinical Innovation nearly always dominate their segments – we consider agents with 10%+ Clinical Innovation to be highly innovative

• Drugs with Clinical Innovation between 5% and 10% typically achieve good patient share – they are moderately innovative

• Drugs with Clinical Innovation below 5% are typically seen as poorly differentiated, especially by payers – these drugs have low innovation

Clinical Innovation and competitive intensity are key drivers of share; our DTA models enter these two inputs into an algorithm derived from a regression analysis of actual market performance to estimate peak-year patient share. Comparing our share predictions to observed peak-year shares, Equinox Group’s oncology-specific regression has a strong R-squared value of 83%.

The DTA methodology is rigorous and dynamic. The Excel-based model we deliver allows for instantaneous updates of inputs and outputs. All sources are well-documented in comments throughout the model, with a bibliographic sources sheet included as well.

Key steps in an Equinox DTA Project

1. Define the distinct patient population(s) of interest

2. Characterize disease burden within each patient population

3. Identify and characterize standard(s) of care

4. Model the market entrant/TPP

5. Analyze the developmental pipeline to quantify the expected future level of competition

6. Estimate the number of addressable patients in the US and key European markets

To support the modeling, Equinox Group also conducts a handful of interviews with academic medical experts to explore their views on pipeline agents, treatment paradigms, and key unmet needs.

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The Clinical Sheet

Equinox Group begins by characterizing the key clinical attributes of the SOC(s). We can then use an identical rule set to model client TPPs. For clients who do not yet have any TPPs, we can help model plausible scenarios for profiles.

In 1L ALK+ NSCLC, the SOC prior to alectinib was crizotinib. (Models normally carry two extra slots to model alternative or future SOCs as needed.)

The key clinical domains are shown in the figure below.

Starting in the efficacy domain, we enter peer-reviewed clinical data for the SOCs. Client TPPs are judged along the same lines. In oncology, key efficacy inputs are:

• overall survival,

• progression-free survival, and

• response rates (partial, complete, and overall)

All inputs are explained in accompanying comments within the Excel file. Academic literature is clearly cited, and any necessary assumptions are explained.

Key safety data are gathered from SOC labels and relevant published trials.

Boxed warnings, frequent or inconvenient patient monitoring, and contraindications and pregnancy warnings (when appropriate) are all taken into account.

Grade 3/4 adverse events are modeled and individually weighted based on their severities (e.g., hyponatremia has a lower impact on unmet need than neutropenia). When substantial adverse event data/hypotheses are available for a TPP, we can model the rates of each event. Alternatively, we can model a simple percentage improvement over a comparator profile (e.g., 20% reduction in the rate of each AE seen in the crizotinib side effect profile). In the example below, full side effect data were available.

The drug or regimen’s convenience score is calculated via a consistent method. Common dosing methods, frequencies, and locations are pre-populated in drop-down menus. The model allows for multi-drug regimens to be modeled, even when combining IV and oral therapies. In this example, each profiled drug is an oral monotherapy.

Finally, the drug or regimen’s annual cost is calculated using U.S. WAC pricing. We use WAC values because they allow fair, transparent comparisons and because net prices are not widely visible.

When patients are on treatment for less than one year, the cost calculation is restricted to time on treatment. In the example below, median time to progression is 10.9 months, so only that fraction of the year is entered in “intended days of therapy”.

The Unmet Need Sheet

The data from the Clinical sheet flow into the Unmet Need sheet (see below); the core clinical assumptions each have their own sub-domain under product need.

Equinox Group staff gather peer-reviewed data on disease burden (disease seriousness and disease cost), and the consistent utility functions are applied in Excel.

Baseline disease seriousness and costs values come from relevant academic literature, and improvements in efficacy flow through to reduce need in these domains.

In this example, alectinib is more efficacious (thus the lower Efficacy score) and has a cleaner side effect profile than crizotinib. Despite a minor convenience disadvantage, its product need score is significantly lower.

The advantage in overall survival is reflected in a lower mortality score.

Advantages in progression-free survival and response rates reduce morbidity, indirect costs, and non-drug direct costs.

These benefits in indirect and non-drug direct costs partially offset alectinib’s higher price.

The weighted sum of these domain-specific unmet need scores equals a product’s total unmet need score. Overall, total unmet need is lower with alectinib than with crizotinib in 1L ALK+ NSCLC, indicating a better therapeutic option.

Drivers of Innovation

We call the reduction in total unmet medical need is called "Clinical Innovation". We graphically display Clinical Innovation using a Drivers chart.

The gold bars to the left and right of the chart represent the unmet need score under the SOC (crizotinib) and entrant (alectinib), respectively.  Scores range from 0-5 with 0 representing no unmet need. As with any waterfall chart, the intermediate green and red bars represent improvements and detriments, respectively, in domain-specific unmet need.

In the above figure, alectinib is shown to reduce total unmet medical need by 23.2%, with more than two-thirds of its improvement coming from efficacy advantages, and its direct cost impact clawing back <1% of its Clinical Innovation. (The percentages on the chart show the contribution of each domain to that 23.2% overall improvement.)

The Clinical Innovation score of 23.2% is highly impressive. Recall our rules of thumb: products with unmet need improvements of >2% are typically commercially viable, >5% are commercially successful (top 3-4 in market), and >10% are market dominators.

The Competitive Environment

Equinox conducts a thorough review of the developmental pipeline using publicly available sources, such as clinicaltrials.gov and sponsor websites. This pipeline is reviewed by physician experts to ensure nothing is missed, and client competitive intelligence is welcomed.

Each pipeline agent is assigned a probability of launch based upon its phase of development and recent data on success probability by phase and therapeutic area. Competitors are also assigned an angle of impact – how directly (25%-100%) will the entrant and the pipeline agent compete with each other?

We call the sum product of these factors “Competitive Intensity”, a probabilized headcount of competitors the entrant will face at launch. A competitive intensity rating of 319%, as shown below, is roughly comparable to three direct competitors at launch.

The Commercial Sheet

Seeing a profile’s projected peak-year share is as simple as one click. Selecting the SOC at launch in the blue cell will automatically update the profile’s clinical innovation score which, alongside competitive intensity, are entered into the Equinox Share Predictor. The Commercial sheet also displays key figures such as unmet need scores with the SOC and entrant, diagnosed prevalence of the indication in the U.S., and the annual cost of the profile.

Given a Clinical Innovation score of 23.2% and a competitive intensity rating of 319%, Equinox Group’s regression-validated algorithm projects a peak-year patient share of 60% for alectinib in 1L ALK+ NSCLC.

Each entrant’s share call compares its unmet need score to that of a chosen SOC and factors in the estimated number of competitors at launch. In this example, product attributes for potential new competitors are not evaluated in calculating peak share. As a further product offering, Equinox builds forecasts that capture the impact of competing entrants’ clinical attributes and launch timing to produce realistic forecasts of share over time.

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Conclusion

The easy-to-use Excel-based DTA model allows clients to war-game scenarios for input values that aren’t certain yet (such as mature overall survival data) and instantly see how those alternatives affect Clinical Innovation and patient share estimates.

Interested in learning more? Click here to send us a message or to schedule a meeting with one of our practice leaders.

Equinox Group’s proven method to measure clinical innovation and peak-year patient share for new products is accurate, less expensive, more flexible, and quicker to execute than conventional market research-based techniques. We use this approach to inform decisions about individual programs (pipeline and business development), to help therapeutic area teams set aspirations, and to inform R&D portfolio assessments.

A project of this nature typically delivers results in around 6 weeks. We support our models for 24 months from kickoff and can help socialize the methodology and results within your organization.

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About Equinox Group

Since 1995, Equinox Group has provided analytics to support R&D decisions at biopharmaceutical firms, assessing the potential of drugs from discovery to launch. Our validated techniques save time and money—and they overcome several deficiencies of traditional demand studies.

We have evaluated thousands of drug profiles across hundreds of indications in oncology, immunology, rare diseases, cardio-metabolic disorders, infectious disease, neurology, pulmonology, urology, ophthalmology, and endocrine disorders. We also have tailored methods to solve the unique analytical challenges that arise in oncology and rare diseases.

Using this methodology, we have developed a suite of tools to inform whatever R&D decisions you’re facing in any stage of development, including: setting indication priorities, supporting go/no-go decisions, assessing market access and pricing potential, share forecasting, and patient flow modeling.