Healthcare & Life Sciences
WHERE CAN AI AID HEALTHCARE AND LIFE SCIENCES?
Healthcare & Life Sciences is clearly a name for a sector that actually spans a wide range of technical specialisms. From pharmaceuticals and biotechnology to healthcare services and medical devices. So the applications of AI will vary wildly.
With extensive first-hand experience across these different organisations, Brightbeam’s founders recognise the dangers of false promises. Instead of presenting AI as a panacea, we focus on how it can solve specific issues that have a direct impact on your organisation’s goals.
Drug Discovery
Operational Issue
Prolonged and costly development cycles are delaying revenues or increasing opportunity costs.
What we can do
Create customised predictive modelling for drug discovery and testing using generative AI tools.
The impact we can make
Accurate and extensive predictions resulting in shortened R&D timelines and reduced costs.
Difficulties in predicting drug interactions and side effects are lengthening R&D cycles and leaving the organisation exposed to future risks.
What we can do
Draw data from multiple sources and developing AI-driven simulations for drug interactions and side effect controls.
The impact we can make
Enhanced ability to test resulting in safer drugs, minimized side effects and faster time to market.
Diagnostics
Operational Issue
Challenges in early disease detection is increasing the burden on acute patient services and treatment costs.
What we can do
Implement AI-enhanced imaging diagnostics for early and precise detection using larger datasets and anomaly indicators.
The impact we can make
Rapid diagnostic clarity resulting in improved patient outcomes as well as reduced public health costs.
An over-reliance on manual interpretation of information is lengthening time-to-diagnosis and prone to more errors.
What we can do
Automate real-time data analytics and reporting by using secure AI to collate, process and report confidential information.
The impact we can make
Near-instant reporting resulting in reduced diagnostic errors among clinicians and faster results for patients.
Clinical Trials
Operational Issue
Inefficient patient recruitment processes are leading to stalled trials or relatively negligible sampling.
What we can do
Dedicated AI algorithms for optimal patient matching and recruitment based on a number of datasets.
The impact we can make
Quick access to a suitable cohort resulting in expedited trials and more funding.
Delays in data analysis and reporting are putting the next phase of the research at risk from budget cuts.
What we can do
Provide real-time data analytics and reporting through adaptive AI tools that can cover multiple trials.
The impact we can make
Flexible yet consistent reporting resulting in efficient trial management and faster time to market.
Patient Care
Operational Issue
Generic treatment plans are restricting the wider success of healthcare programmes.
What we can do
Apply AI tools to establish treatments that are tailored to the individual.
The impact we can make
Personalised approach resulting in higher patient recovery rates and satisfaction scores.
Fragmented patient records are creating an administrative burden for an organisation judged on healthcare outcomes.
What we can do
Integrate and cleansing record management system data while layering AI to enable staff to request a range of reports.
The impact we can make
Seamless record management resulting in coordinated care pathways, improved patient outcomes and a lower cost to serve.
