Improve the outcome of your global clinical trial with AI translation
Artificial intelligence can boost clinical trial success rates and speed up time to market. Are you leveraging the full power of AI translation?
Bringing a new drug to market can be a protracted, painstaking, and often costly process. The scale and complexity of this challenge increases significantly when a clinical trial involves numerous countries and translation into several languages—as they often do in modern healthcare investigations.
Recent advances in artificial intelligence (AI), however, are transforming the way clinical trials are conducted and are having a massive impact on their success rates and cost-effectiveness as the time-to-market is dramatically reduced.
What is Artificial Intelligence?
Artificial intelligence describes a broad collection of computer engineering solutions designed to perform tasks traditionally considered to be typically human, such as problem solving and pattern recognition.
The development of sophisticated data-gathering software and high-performance processing technology has led to a proliferation of AI applications. Tasks that once would have involved an insurmountable volume of data processing are now possible at the touch of a smartphone (consider the data processing involved in a phone app as it provides instant car navigation to the driver).
One branch of AI is machine learning (ML)—systems that automatically adapt their actions as they acquire new data (such as the efficacy of previously processed actions).
Within ML is deep learning (DL), which uses artificial neural networks (algorithms inspired by human brain activity) to absorb information from multiple data sources, analyze it in real time, and progressively ‘learn’ and improve the accuracy of the outcome.
It is deep learning that has driven many of the AI advances in healthcare, particularly clinical trials.
How is artificial intelligence used in clinical trial translation?
Despite the significant investment of time, money, and resources, clinical trial success rates are low. A report analyzing clinical trials carried out between 2000 and 2015 found that only 13.8% ended in success.
The reason for failure is not always medical. Flawed trial design, patient drop-out, and the unsuitable recruitment of participants are all common explanations for the collapse of a clinical trial. Looking at patient drop-out alone, recent research shows that a staggering 85% of clinical trials fail to retain enough patients for the full duration of the trial. The costs of this—in terms of time, money, and medical setbacks—is enormous.
AI is reinventing the process of patient selection, patient monitoring, and data translation for clinical trials, ensuring time, money, and resources are deployed effectively and useful trial data is more likely to be acquired at the conclusion of the trial.
AI in Patient Selection
Recruiting participants for a trial begins with a search for eligible people among the population. This involves analyzing and cross-correlating a number of data sets (age, medical history, height, eye color, blood type…). This group then needs to be optimized further by, for instance, identifying those most incentivized to participate for the full extent of the trial.
AI’s ability to automatically process vast datasets from a variety of sources (involving text, images, and audio) at incredible speeds is transforming patient cohort composition. As a result, trial effectiveness and its chances of reaching a successful conclusion are drastically improved.
AI in Patient Monitoring
Participants must adhere to the correct procedures and provide feedback throughout trials. For example, they are often required to maintain detailed records of their medication, food intake, and bodily functions. This can become a tedious and easily neglected task, especially when trials last for many months.
AI, however, can relieve the patient of this burden by using wearable sensors and video monitoring to gather real-time information automatically and inconspicuously.
AI in Data Translation
Global clinical trials that take place across several countries require the translation of a large amount of documentation, data, and analysis. This is a critical stage for any medical research as there is no room for misunderstanding or ambiguity in the information being translated.
It is crucial that the same level of accuracy and attention to detail present in the original source material is maintained in the target material. Every textual nuance, cultural difference, and technical convention (such as the formatting of dates and units of measurement) must be created with absolute precision. This is where the use of AI is especially valuable.
Artificial intelligence is used to build a ‘translation memory’—a database of relevant, ready-translated words and phrases. The AI then analyses the source text and automatically identifies groups of words that match those in the translation memory. Unlike simple word-for-word conversion, the AI uses its ‘knowledge’ of other relevant translations to recognize the context of each word and phrase. As a result, it can accurately replicate the meaning and context of the original material.
Globalize your clinical trial translation with AI
There are scientific reasons why clinical trials are conducted across the globe. Most obviously, the findings will be more authoritative if data has been collected from a diverse range of ethnic groups and the methodology has been shown to be safe and effective in geographically dispersed trial sites.
There are other reasons too why researchers might choose to carry out their trial internationally. Some countries are able to recruit participants faster than others, for example.
The application of AI in clinical trials is particularly valuable when they take place globally, as Lea Backhurst, Nordics Managing Director at AI translation specialists Summa Linguae Technologies (SLT) explains:
“To speed up the translation process of global clinical trials and shorten the time to market, it is essential to maximize the opportunity that AI presents. At SLT, we take a multifaceted approach, using the latest AI technology to: build a glossary of terms specifically related to the product; utilize extensive, ready-made, industry-specific translation memories; and create a tailor-made deep learning machine translation solution combined with post-editing by expert medical reviewers.”
Advances in AI have made it possible to gather and process more data from clinical trials than ever before. It has also transformed the way trials are conducted, particularly when conducted across different countries.
If you feel the issues touched on in this article could make a difference to your next clinical trial, contact SLT to discuss an AI solution that will boost your trial’s chances of success and accelerate delivery to market.
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