Technology on trial – the latest cogs in the clinical machine
pharmafile | February 1, 2022 | Feature | |
From the integration of social media to everyday life, to the seeping of AI into our daily lives, the past two decades have seen significant leaps in technological innovation around the globe. While clinical trials have previously proven hesitant to utilise the technologies available, the landscape of clinical technology is changing constantly – proven by the reflexes the industry showed from the outset of the COVID-19 pandemic. However, AI, e-technology, and other advances in the digital age all introduce challenges as well as benefits when implemented in a clinical trial setting.
‘E-technology’ describes digital and electronic technology that utilises mobile devices or the internet. With the introduction of e-technologies into a clinical setting, the drawbacks complicate many of the advantages. Issues such as patient data safety, ethical matters, attendance, and patient compliance, ensure that developments in clinical settings are by no means straightforward.
In the midst of a pandemic, the increasing implementation of e-technologies and telemedicine have ensured greater connectivity in a time of isolation. Telemedicine refers to the remote diagnosis, treatment, and distribution of health services via electronic technologies. The implementation of digital technologies may also allow for easier recruitment in trials, via social media channels, such as the 2020 NHS campaign to test for COVID-19 antibodies. Tools to increase patient recruitment have proven vitally important even prior to the pandemic; in 2016, a report on cancer trials shared that around 20% failed because of poor or inadequate levels of patient recruitment.1 In many instances, technology has been forced upon companies in the wake of the pandemic. It remains to be seen which innovations are only adaptations to COVID-19, and which are here to stay on the trial scene for years to come.
For the record: clinical trials and electronic health
An area of increasing interest is the use of electronic health records (EHRs) in clinical research. Integrated systems can avoid duplication of data entry, and EHRs are an important resource for identifying and recruiting patients for clinical studies. The use and streamlining of these records can ensure faster recruitment processes, allowing clinical trials to begin sooner, and ensuring much-needed medicines can reach approval faster, and potentially address areas of high unmet patient needs.
Sensyne Health, which at the time of writing is facing liquidation, is one company utilising EHRs in clinical research. The ethical clinical AI company has partnered with Cambridge University Hospitals NHS Foundation Trust (CUH), for the ethical application of clinical AI research. The partnership will see the analysis of de-identified patient records in order to carry out research. Under the agreement, Sensyne and CUH will use AI for the analysis of retrospective clinical data, and support the generation of synthetic control arms to aid clinical trials more effectively, accelerating the drug development process. The agreement will also focus on drug discovery, helping to discover new medicines aimed at treating rare and common diseases, including cardiovascular disease and cancers. The CUH dataset covers three million unique patient records, with roughly one million patient contacts per year from a patient population of approximately five million people.
Dr Ashley Shaw, CUH Medical Director, shared: “By searching large de-identified datasets, machine learning tools can spot patterns which are otherwise indiscernible, shedding light on causes of disease and opening up new treatment opportunities.”
On a roll with machine learning
The integration of AI and machine learning (ML) into clinical trials has the potential to help drugs reach approval faster. Further down the clinical trial line, new technologies are also being utilised in various areas, including for rolling reviews.
Accord Healthcare are working to minimise risks associated with the treatment of multiple myeloma, monitoring the use of generic lenalidomide. In doing this, Accord will oversee a robust protection system to support safe prescribing, including a strictly monitored ‘Pregnancy Prevention Programme’, and an e-portal for healthcare professional (HCP) use. This electronic portal aims to facilitate more improved pharmacy registration and prescription authorisation.
The company is accounting for the differing needs of HCPs by providing additional risk minimisation materials in paper-based formats. This support comes alongside investing in the development of digital technologies to improve the mandatory processes, which must accompany the medicine. The move counters some of the disparities, such as age, that arise with the use of digital technology in healthcare.
(Artificial) intelligence, imaging, and innovation
Pharmafocus spoke to Jean-René Bélanger, CEO of Imeka, who commented on the potential of the use of AI in clinical trial settings: “AI enables us to look for markers of disease in a non-invasive way in clinical trials. Where other markers would be extracted from cortico-spinal fluid using a spinal tap, we can attain the same results using non-invasive MRI technology, making the patient’s experience in a clinical trial much better.”
Imeka is a leading neuroimaging company that is collaborating with Atara Biotherapeutics to provide neuroimaging for a Phase II study. The study will investigate the potential effect of Atara’s treatment for multiple sclerosis (MS), ATA188. ATA188 is currently being evaluated in a Phase II study in the US and Australia in patients with primary progressive MS, and secondary progressive MS. Imeka’s non-invasive advanced neuro imaging endpoints (ANIE) biomarker platform will measure the potential effect of Atara’s investigational treatment on neuroinflammation and remyelination in the brain and spinal cord.
Diseases like MS present significant challenges to diagnosis and treatment. The integration of technologies like ANIE into a clinical trial setting can pave the way for improved disease measurement and treatment efficacy.
“There is a well-known “clinico-radiological” paradox in MS diagnostics,” shared Bélanger, “which is that classical MRI metrics of lesion load do not correlate well with clinical outcomes. Some patients have a lot of lesions and very few disease symptoms and vice versa. Technologies such as Imeka’s allow us to look in places that were previously unexplored. White matter that appears normal via traditional methods can now reveal inflammation or demyelination.”
The integration of such technologies with clinical trials, to investigate the effects of treatment for devastating diseases, has a potentially seismic impact on the lives of patients:
“There are two main ways that AI in imaging can help accelerate analysis of new treatments for neurodegenerative diseases like MS,” Bélanger added. “First, by accelerating image processing of new datasets. We are dealing with thousands of images to process in each clinical trial. It used to take more than 48 hours per image to process. With the advent of AI, we have developed new algorithms that enable that process to be completed in less than 20 minutes by speeding up critical parts of the image processing pipeline.
“The second way is by determining what a ‘normal’ brain looks like with a very large number of images from a very large number of patients with an even larger number of characteristics in each of these images. We can then compare a new patient with that dataset and very quickly identify deviations in subtle parts of the brain.
“When imaging and AI are combined together, we can identify the efficacy of new drugs in much more subtle changes in the biology of the brain, which means shorter trials with fewer patients, and thus quicker analysis of the treatment.”
Streamlining trials means drugs may be brought to the market faster, bringing about significant changes to the lives of patients sooner. Biomarkers and AI platforms in clinical trial settings contribute to this streamlining. Bélanger said: “Effective biomarkers can be used much earlier in the development of drugs and treatments, which enables clinical trial investigators to gain information about the efficacy of an investigational treatment in earlier study phases. This allows for other candidates to be tested quicker and good candidates to emerge on top faster, making the overall drug development much quicker and more cost-effective.”
Pre-trial, e-learning
Digital innovation can be brought in at all stages of the trial process. The first group of psychotherapists has begun training for a clinical trial using psychedelics and therapy in treatment resistant depression (TRD). They are involved in a Phase II clinical trial, which will examine 5-MeO-DMT, an assisted psychotherapy for TRD. Initial elements of the training programme will feature online, interactive, self-taught modules, followed by live, in-person training sessions hosted by the Kadima Neuropsychiatry Institute in San Diego, US. This comprehensive programme aims to cause meaningful change in those suffering from severe mental health disorders.
The training is being carried out in collaboration with Fluence, an expertise-driven education platform, providing professional training in psychedelic therapy for psychiatrists, psychotherapists, social workers, and other HCPs. Beckley Psytech is a private company dedicated to addressing neurological and psychiatric disorders through the novel application of psychedelic medicines.
Innovation meets complication
As new opportunities for improving patient care through technological innovation are developed, fresh concerns for patient safety and security arise. Incorporating digital technology into the clinical trial sphere often proves difficult, due to the exponential rate of growth of many technologies, vs the arduous process of drug research, development, trial, and manufacturing. With the impetus to introduce further technologies to the clinical trial scene, the question arises: how can policy keep up with change?
Telemedicine makes it harder for patients to ask questions, or gain as thorough an insight of their treatment as they would gain while being informed face-to-face. Recruiting participants from online platforms also means further accounting must be done for variables of region and culture, where diet, daylight, and activity can all impact patient outcome.2 Threats to patient privacy and confidentiality are also introduced with the incorporation of e-technology into clinical trials, alongside disparities according to factors like wealth and age bracket impacting technology use and literacy. While 84% of adults use social media sites, fewer than half of those aged 65 and older reported to do so in a study conducted in 2021.3 With the use of mobile devices, it is critical to standardise reliability, sensitivity, and specificity of measurements.
There is, finally, a poverty of regulatory guidance and policies around the use of technologies and clinical trials, and as e-platforms are constantly evolving, legislation around these settings often struggles to keep up. Exponential technologies – technologies expanding rapidly – include VR, and the IoT. Innovations falling into this category are particularly difficult to regulate and introduce into a clinical setting.
Conclusions, implementations, and implications
The introduction of more technology in clinical trials may increase engagement not only through the vital initial stages of patient recruitment, but also through patient compliance, and the reduction of patient burdens. The implementation of technology in a healthcare setting comes with many complications of security, equality, and specificity. Data collection, recruitment, and retention can be improved exponentially with technology – saving time and money, and technology such as AI may even be used to design and implement the trials themselves.
Incorporating medical innovations and systems can significantly improve the outcome and efficacy of clinical trials. This innovation, in turn, improves patient experience, standard-of-care, and medical accuracy.
Clinical trials are slowly adapting to the benefits of new technologies. Whether it is deeper analysis of electronic health records, or reducing burden of patients with telemedicine, there is value in the continued evolution of this vital area of the drug development and approval process.
Ana Ovey
References
- www.fdamap.com/about-20-per-cent-of-cancer-clinical-trials-fail-due-to-low-patient-recruitment.html#:~:text=About%2020%25%20of%20Cancer%20Clinical%20Trials%20Fail%20Due,find%20patients%20willing%20to%20participate%20in%20their%20trials
- www.ncbi.nlm.nih.gov/books/NBK396107
- www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021
