Algorithms are already having an impact on the pharma and life sciences industries. Start-ups are pushing the boundaries in areas such as AI and machine learning. We’re entering the Age of the Algorithm – but how can the industry make the most of this?
In a consumer-driven society, the demand for pharmaceutical organisations to meet patient demand is increasing, and new technology trends have emerged to account for this ‘always on’ mentality. Sharing information and data has become an everyday norm for many, and now drives our social lives, the political agenda and most organisations and businesses.
Nearly everything we do in this connected world produces data, which is then sequenced, decoded and analysed by machines to provide us with useful information to identify patterns of behavior and make correlations and predictive assessments.
So how can the life sciences industry benefit from this digital age?
Technology is moving at a rapid pace, allowing us to understand and treat illnesses with a higher degree of accuracy, through precision medicine and data-driven insight. Technologies like big data and machine learning are changing the way certain industries operate, and within healthcare it is arguably coercing us to redefine “diagnosis” and “treatment”.
Pharma and life sciences organisations are looking for ways to embrace this technology intelligently, with the C-suite craving innovation to meet the growing demands of its patients. We’re seeing technology giants like Google using data to predict a flu epidemic before it happens and doing so much faster than the authorities through analysis of search terms. Imagine if Google had a pharmacy – it would outstrip the outdated pharma models to embrace big data for good.
A recent Gartner report on Business Drivers of Technology Decisions for Life Sciences (opens in new tab) identified both digital business and digitisation as top priorities for C-level executives. These are both critical for incubating innovation within the product lifecycle itself, reducing costs and bringing products to market more efficiently – ultimately redefining healthcare for the better.
However, Gartner also highlighted that many industry leaders are not yet confident in their ability to gain beneficial results from their digital transformation efforts (opens in new tab), and perhaps rightfully so. Organisations lack the resources, insight, and capabilities to successfully roll out this technology, and are unable to articulate to the wider-business why it is important. This is where low-code comes in.
Low-code puts application development in the hands of IT users and this can be extremely beneficial. Intense regulation means life-preserving drugs and therapies can take years to come-to-market. But in the fast-moving world of pharma, using off the shelf software such as Excel to track all compliance needs is like innovating with one hand tied behind your back.
Low-code helps workers in the pharma industry build their own applications that circumvent such problems and bring drugs to market much faster. It can also work alongside emerging technologies like robotic process automation (RPA) and AI to help streamline drug development processes and leverage data to inform lifesaving decision making. This technology also helps to bridge complexity, which is rife in the pharma industry, without having to radically change the process while ensuring end-to-end control.
We are already seeing heavily regulated industries, such as insurance and financial services, embracing this technology. Aviva is already using low-code technology to develop applications and create automated systems matching the skills of employees to specific cases. The company has seen a 40% increase in efficiency since implementing Appian's low-code platform and has since applied the same automation to wider areas of the business.
To support the speed and accuracy of diagnosis for diseases like cancer, technology such as AI and machine learning must be embraced and used on the front line to help further reduce diagnosis time. Traditional approaches to interpreting patient information relies heavily on human input, and are not suited for high-volume, routine clinical testing. The most respected oncologists, medical specialists and clinicians know that only with the highest degrees of accuracy, repeatability and reproducibility will lives be saved.
For example, using AI and machine learning techniques, healthcare professionals can more efficiently diagnose a specific type of cancer and based on the vast amounts of data to hand, offer a more personalised treatment, compared with traditional medical practices. This leads to higher survival rates for patients and a more efficient treatment process for practitioners.
Low-code: Enabling faster development and time to market
With an informed digital transformation strategy and execution plan, life sciences organisations can reap the benefits of streamlined processes, including a simplified product lifecycle, faster time to market, easy-to-maintain regulatory compliance, and cost savings throughout.
This digital transformation also leads to increased customer engagement, which is beneficial at the very beginning of the drug development cycle. Gathering patient input is the best way for organisations to design clinical trials that will meet the needs of all stakeholders.
The insights gained by achieving patient input can be applied at every stage of drug development and delivery, from compliance and R&D, to labelling and distribution. This enables life sciences organisations to bring drugs to market that better reflect patient needs and help patients and providers achieve better results.
The introduction of innovative technologies to the life sciences industry not only benefits the patients, but the entire drug development process as well. By incorporating big data analytics, RPA and AI, and streamlined process management systems, organisations can maintain efficient, patient-friendly and cost effective clinical operations.
Healthcare professionals have never had so much data at their fingertips, and much is being done to crunch this data behind the scenes to provide accurate diagnoses. Through innovative solutions coupled with human expertise, technology is accelerating routine clinical use of data for better diagnosing and treating patients through specific care paths.
The Age of the Algorithm is upon us and it is time for the pharma industry to embrace the technology available.
Stefan Prebil, Pharma Practice Leader, EMEA at Appian (opens in new tab)
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