HTA Lab projects

Current projects

Artificial intelligence (AI) in HTA

AI is expected to have transformative applications in many areas of healthcare. We have already produced guidance on AI-enabled health technologies. There are also ways that AI might be used to inform evidence about health technologies.

In collaboration with teams across NICE, we’ve led on the development of the use of AI in evidence generation: NCE position statement. This sets out our view on the use of AI methods in the generation and reporting of evidence considered by our evaluation programmes. The position statement seeks to ensure their use is justified, proportionate and transparent.

We’ve also started an HTA Lab project to explore how generative AI techniques might be used to inform all aspects of economic modelling, from development to validation.

Comparing the environmental impacts of health technologies

We’re looking into how feasible it is to assess the environmental impacts of competing medicines and health technologies where there’s little or no expected difference in health or cost outcomes. In such cases, it would make sense to choose the option that’s better for the environment. We’re hoping to find a proportionate and pragmatic way to do this, bearing in mind that data and methods in this can area change quite quickly.

If we can identify a suitable approach, we’ll look into conducting a pilot evaluation.

This kind of evaluation would be consistent with the findings of our NICE Listens deliberative public engagement dialogue. This explored views on our role in making healthcare more environmentally sustainable.

Enabling individualised therapies - challenges for HTA

Individualised genomic therapy is a potentially transformative field in medicine, offering tailored treatments based on individual patient characteristics and genetics. The anticipated pipeline of technologies that enable highly individualised therapies may pose significant implementation challenges for the healthcare system. It is important for NICE to consider its role in evaluating these technologies.

This project aims to gain a clearer understanding of the technologies that enable individualised therapies, their development pipeline, and the associated challenges.

To achieve this, we will:

Focus on nucleic acid therapies, as a prominent type of emerging individualised therapy.
Engage with system partners and stakeholders.
Examine the clinical evidence underpinning personalised therapeutics.
Identify issues related to assessing clinical and cost-effectiveness in previous HTAs and published literature reviews, and consider their implications for NICE’s standard medicines evaluation processes.

This work will identify the challenges involved in emerging individualised treatments, designed around a patient’s specific genetic or molecular profile. Ultimately, it will strengthen NICE's capacity to appraise these treatments, supporting timely patient access to innovative therapies.

Examining the methods for capturing implementation costs

Innovative medicines and health technologies sometimes require new healthcare infrastructure or redesigned services to support their implementation. For example, new diagnostic services might be needed to identify eligible people, or physical infrastructure may need to be built to administer treatments.

These implementation costs could be very high, affecting conclusions about the technologies’ cost effectiveness. NICE’s current methods do not provide detailed guidance on when and how these costs need to be incorporated. So, this project will:

Examine existing methodological approaches to include implementation costs in health technology evaluations and assess their appropriateness from a NICE perspective and their acceptability by different stakeholders.

Outline a preferred approach for incorporating implementation costs into NICE’s evaluation methods informed by two case studies.

This project aims to increase consistency and improvements in how implementation costs will be considered across our evaluations, further contributing to ensuring that NICE’s recommendations represent good value for taxpayers.

Expanding the Antimicrobial Products Subscription Model

We urgently need new drugs for infections that are resistant to existing treatments. But investing in new antimicrobials is not commercially attractive because, to slow the development of resistance, drug usage is restricted. Meaning sales are low.

The UK healthcare system’s subscription payment model, co-developed by NICE and NHS England, incentivises antimicrobial development by guaranteeing companies a fixed annual payment for their drug, regardless of volumes sold.

The subscription model is open to traditional antibiotics, but extending it to other antimicrobials (such as antifungals, non-traditional antimicrobials and treatments for drug-resistant tuberculosis) would enhance its impact.

Exploring this expansion in the HTA Lab’s ‘safe space’ environment will ensure the initial implementation for antibiotics remains unaffected. This project involves identifying priority antimicrobial products and adapting NICE's evaluation criteria and scoring system appropriately. This could enable the subscription model to include a wider range of products, which would stimulate investment in new drugs for the NHS to keep pace with rising antimicrobial resistance.

Novel data sources in HTA

Innovative medicines and health technologies are increasingly likely to be underpinned by novel types of evidence such as laboratory-based (in vitro) data, real-world data from wearable devices, and simulation-based (in silico) data. Technological advances and the need to address the limitations of traditional clinical trials are driving this shift in the evidence landscape.

NICE does not routinely encounter or actively seek novel data types in its technology evaluation programmes. However, such data could provide additional evidence that helps NICE’s committees to make fully informed and more relevant recommendations.

This project aims to:

examine the existing and potential uses of different types of novel and non-traditional data for HTA
identify current challenges that these types of data may be best positioned to resolve.

This work will immediately support NICE and its stakeholders in using or reviewing the examined types of data. It may also inform future case studies to examine the most promising uses in more detail.

The future of HTA with AI

This project explores how AI might support and evolve NICE’s health technology assessment (HTA) processes. As AI capabilities advance, there is growing interest in how tools such as automation, predictive modelling, and reasoning systems could contribute to more efficient, responsive, and proportionate approaches to evidence evaluation. However, the integration of AI into HTA also raises important questions about feasibility, transparency, and methodological rigour.

Through stakeholder engagement, workflow analysis, and proof-of-concept demonstrations, this project will identify and prioritise potential AI use cases across the HTA lifecycle. It will also consider the practical and ethical implications of AI adoption, and the conditions under which such tools might add value.

The project will culminate in a shared vision and implementation roadmap. It aims to ensure NICE remains prepared and adaptive in the face of rapid technological change, while maintaining its commitment to robust, evidence-based decision-making.

Past projects

Disease modifying dementia treatments

New disease modifying dementia treatments (DMDTs) are anticipated to alter disease progression and change the management of Alzheimer’s disease.

To help NICE medicines evaluation team prepare, the HTA Lab conducted a project to identify the key issues that are likely to emerge during the evaluation of these treatments. This was informed by input from patient organisation groups, our partners and international HTA agencies.

Further detail of this work is included in this first report from the project (PDF).

The HTA Lab also explored how implementation costs for new infrastructure and NHS services might be captured when evaluating first-in-class therapies. Further work looking at this subject is recommended. Further details are available in the second project report (Word).

Metabolic dysfunction-associated steatohepatitis (MASH)

The emerging pipeline of treatments for metabolic dysfunction-associated steatohepatitis (MASH) offers promising therapeutic prospects. However, it also presents significant challenges for health technology assessment and implementation.

MASH affects a diverse and possibly very large group of patients. And with no approved treatments available for it right now, it represents a new therapeutic area for NICE’s technology evaluation programmes.

This project sought to identify and examine the potential challenges in evaluating MASH treatments. By collating findings from a thorough review of the current clinical landscape (Word) for MASH, performing a systematic review of published economic evaluations (Word), and leading engagement with various stakeholder groups (Word), the HTA Lab team has developed an economic model concept for evaluating MASH therapies (Word).

The findings from this project will improve the consistency of future economic models in this area, and support NICE to appraise MASH therapies in a robust and timely way.

Methods for the evaluation of diagnostics used in multiple care pathways

The number of AI and genomics-based technologies that can be used in multiple disease areas or at multiple positions in the disease pathway ('multi-indication' technologies) is increasing.

Evaluating multi-indication technologies is likely to pose a challenge to the current NICE Diagnostics Assessment Programme (DAP) methods and processes.

The first stage of this project is now complete. The team has produced a report that outlines a potential approach for evaluating multi-indication technologies (Word), ensuring their value is appropriately captured.

If you are the developer of a multi-indication technology, and are interested in working with us on a pilot prioritisation exercise to identify use cases for modelling, please contact [email protected].

Rapid entry to managed access (REMA)

As part of NICE work to develop a proportionate approach to technology appraisals, we looked at a new approach to appraising medicines which were highly likely to need a managed access agreement.

We ran a project to examine the feasibility of developing a process to allow REMA for medicines with uncertain evidence.

Currently, these medicines undergo a full appraisal before being recommended for managed access (MA), and another at the end of the MA period. A more streamlined process for evaluating these medicines can mean more timely access for patients.

The HTA Lab: rapid entry to managed access project report (Word) provides more information on this work and its findings. These will inform further work by NICE in this area.

Using real-world evidence from managed access: a review of cancer appraisals

The Systemic Anti-Cancer Therapy (SACT) dataset has the potential to provide valuable information to NICE committees, addressing uncertainties in key outcomes during re-appraisal following a managed access agreement. However, there is a lack of guidance about how SACT data should be used during an evaluation, which may lead to inconsistencies.

Working with the Decision Support Unit (DSU), the HTA Lab reviewed how data from SACT were used in a sample of appraisals that have exited the Cancer Drugs Fund. This has led to pragmatic recommendations for how NICE can routinely use available SACT data more consistently to give committees a clearer picture of the overall uncertainty, as well as some suggestions for improved use of SACT data in the future.

Details of this work and our recommendations are included in the project report (Word).

Virtual wards

Virtual wards (also known as hospital at home) allow patients to get the care they need at home safely and conveniently, rather than being in hospital.

The HTA Lab has contributed to the development of NICE guidance on virtual ward platform technologies for providing virtual wards for people with acute respiratory infections.

The HTA Lab team has also completed a review of the published economic evaluations of virtual wards (Word) and a report on target product profiles (Word).

Find out more about NICE’s work to support implementation on virtual wards.