Sanobar Syed

Overcoming Forecasting Challenges in Cell and Gene Therapies

By Sanobar Syed
Sanobar Syed

Predicting the potential of cell and gene therapy pipelines presents unique challenges. Following are considerations for forecasters working with novel technologies.

Forecasting is a vital activity that supports a range of key business decisions across a broad range of stakeholders in pharma and medtech. And it is not just about crunching numbers; it’s about interpreting data effectively and using it to make informed decisions promptly. With the integration of machine learning, predictive analytics, advanced analytics software and artificial intelligence (AI), forecasting has evolved to meet the demands of a dynamic landscape, especially with the rise of competition and significant M&As, which have added layers of complexity, particularly in the realm of innovative cell and gene therapies (CGT).

Novartis and Kite pharma have been at the forefront of developing ground-breaking GCTs, such as Kymriah and Tecartus. The success of these therapies underscores the importance of accurate forecasting — especially when they are first to market in their respective indications and analogs are scarce — in navigating the complexities of bringing revolutionary treatments to market.

Anticipation surrounding CGTs is palpable. However, significant hurdles remain in making these treatments cost-effective and globally accessible. The allure lies in the possibility of curing diseases with a single treatment, which has sparked considerable interest. As per the CGT Manufacturing Market research by Future Market Insights, the global market reached a valuation of around $19.3 billion in 2023 and is expected to surpass a valuation of around $240 billion by 2033 with a CAGR of 29% from 2023 to 2033. Forecasts suggest that the CGT industry will soar with regulatory approvals expected to increase, particularly in key markets including the U.S. and Europe. Despite economic uncertainties, investment in this sector remains robust, driven largely by venture capital, fostering a vibrant ecosystem of innovation in biologics.

Entering this sector involves assessing clinical benefits against current standards, patient pool, patient journey, and market competition (crucial for firms with a single asset or limited resources). Careful evaluation of whether to go with build, partner or buy decisions is essential due to the complex drug value chain. Forecasting also guides investment strategies amidst revenue volatility and unique payment structures based on geography.

Here are the top three considerations for forecasters in the CGT space:

1. Pre-clinical to Pre-pipeline Potential: Predicting the potential of CGT pipelines presents unique challenges due to the specificity of genomic targets, high unmet needs, and relatively small patient populations. Most importantly, since many new approved products are first to market, there is a scarcity of analogs or similar market comparators which are typically used by forecasters to develop market uptake assumptions. Success hinges on adeptly forecasting the effectiveness of the therapy against traditional modalities and standards of care, and the ability to lower costs, develop superior delivery methods, and scale up production.

With so many CGTs in the pipeline, it is essential to reflect on the forecasting imperatives and overall organizational goals (brand priorities). Aligning forecasting efforts with organizational objectives is essential for developing robust forecasts that inform successful launch strategies amidst a crowded pipeline.

2. Quality of Life (QoL) and Duration of Treatment (DoT). Traditional metrics, such as QoL and DoT are less relevant to the forecasting process for CGTs, which often offer one-time treatments, compared to other pharmaceuticals or devices. However, capturing patient drop-off throughout the treatment journey remains crucial for accurate forecasting.

3. Keeping pace with innovation. As large life sciences companies become more immersed in GCTs, they will be — and are — working on multiple technologies concurrently and placing bets on multiple platforms and technologies. Data collection is paramount in forecasting. There is software that will take the patient level data and synthesize information for the forecaster to use. It is critical to integrate this real-world data into the forecasting model. When forecasting for novel technologies, forecasters must draw on their expertise and judgment. A strong foundation of scientific knowledge is essential for understanding terminology and delivering precise forecasting outputs, particularly when analogs are scarce.

Despite ground-breaking innovation in the CGT space, substantial unmet needs persist. Forecasters play a pivotal role in ensuring organizational success by understanding market dynamics and delving into relevant factors to build robust forecasting platforms that facilitate informed decision-making and a successful product launch.

Additional Resources:

1. Krishna D, Rittié L, Tran H, Zheng X, Chen-Rogers CE, McGillivray A, Clay T, Ketkar A, Tarnowski J. Short Time to Market and Forward Planning Will Enable Cell Therapies to Deliver R&D Pipeline Value. Hum Gene Ther. 2021 May;32(9-10):433-445. doi: 10.1089/hum.2020.212. Epub 2020 Nov 2. PMID: 33023309.

2. Delfi Krishna: How to Compete in the Gene Therapy Market | MIT Sloan Health Systems Initiative | MIT Sloan

3. Forecasting the Future of Gene Therapy in 2024 (

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Sanobar Syed