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BearingPoint’s Claudia Carr examines the healthcare sector’s future needs and the importance of adapting to new technologies.
Most of us regularly visit our pharmacies to either purchase an over-the-counter pain killer or have a prescription filled. For the most part we expect the relevant medication to be readily available.
The majority of medications are designed to meet the needs of the broader population, based on years of research, testing and clinical trials. However, they also typically come with warnings about potential adverse effects and sets of pre-conditions outlining circumstances in which the medication should not be used.
The reality is that what is effective for one person may not be effective for another. Through trial and error, we learn what works best for us, and a prescribing clinician will often consult a patient to understand if they have previously had a negative reaction to a specific treatment in the past.
In the majority of cases, these reactions may represent a minor discomfort, however according to the OECD, as many as one in 10 hospitalisations may be caused by a medication-related event. Moreover, these events can have serious consequences for patients’ health and quality of life, leading to disability, morbidity or mortality. The cost of adverse reactions, or misuse of medications, to the Irish health sector alone is estimated to be close to €200m per year.
In addition, a significant percentage of those taking multiple medications per day will be required to take another medication to manage the side effects of other medications.
There are a number of different ways in which IT systems and data can be used to reduce the risk of adverse reactions and improve the overall outcome for patients. This includes the use of technology to better understand the specific needs of a patients, track and monitor their reaction to different medications and improve the development of treatments. This data can provide researchers, clinicians, and manufacturers with the insights to determine a more appropriate and tailored approach to treating patients.
Understanding patient needs
It is well recognised that prevention is better than cure. National health strategies will often focus on improving the wellbeing of a population as a whole and aim to decrease the incidence of serious disease. This includes increased levels of screening and monitoring of risk factors that may lead to the development of a serious medical condition.
Genetics can play a significant role in determining how individuals respond to medication or medical devices, and whether they experience adverse reactions or side effects. Biomarkers – biological indicators that can measure the presence or activity of a disease – can help diagnose diseases, predict outcomes, monitor progress and select the most effective therapies for each patient.
DNA testing and genome sequencing has become increasingly available to both clinicians and patients alike. Various commercial business offer DNA sequencing services, which will provide insights into risk levels of developing medical conditions in the future. This information can be used by patients to take preventive actions or apply lifestyle changes to manage risk. The insights from these tests can also be used to inform future screening programmes leading to the earlier detection of conditions.
Multiple tests are now also available to analyse gut microbiome which can also be a key indicator of health outcomes. The gut microbiome also interacts with other organs and systems in the body, such as the brain, the liver, the skin and the endocrine system, influencing various aspects of physiology and behaviour.
Therefore, environment and lifestyle also play a role in treatment outcomes. Understanding the mechanisms and effects of the gut microbiome on health and disease is crucial for developing new and personalised biotechnology solutions for prevention, diagnosis, and treatment.
Monitoring and tracking reactions to treatments
Traditionally drug manufacturers have used clinical trials to capture insights into how different cohorts of the population react to a medication. Data is collated over time. Once a medication is being supplied on the open market, additional insights will come from adverse reaction reporting.
However, technological advancements mean that there is significantly more data available to understand the wider factors that may contribute the success of an individual treatment plan. In addition to genomic testing, monitoring tools including wearables to monitor activity levels and biomarkers, and improved connectivity have resulted in a greater level of data to understand the impact any individual treatment plan.
Digital health can help provide real-time feedback, guidance and support to the patient and the healthcare provider, as well as to collect and analyse health and wellness data, such as vital signs, activity levels, and mood. Several apps have been developed to support those with various chronic diseases to monitor their symptoms and build an understanding of the factors that may leads to an escalation of symptoms, including capturing real-time insights into the impact of medication and any associated side effects.
With improved insights and the application of AI and data analytics, it is now possible to develop better insight into the most effective treatment plan for a patient based on a range of different factors.
The role of personalised medicine
One of the most significant trends in biotechnology is the emergence of personalised medicine, which is the tailoring of medical treatments to the individual characteristics of each patient. Personalised medicine relies on the use of biomarkers. This offers several benefits, such as improved efficacy, reduced side effects and lower costs of treatment.
Although commonly used for the treatment of specific conditions such as tumours, with improved data insights it is likely that the demand for more personalised medicines with continue to grow. However, it also poses some challenges, as well as the need for more data and infrastructure to support its development and implementation.
Achieving this however introduces both operational and regulatory challenges for the health sector and those developing treatments.
As sources of information increase, so too does the volume of information captured. One of the key challenges for researchers is identifying the most relevant data to make informed decisions. AI can support but is dependent on the appropriate amounts of data to learn from and make predictions. Therefore, it is essential to have high-quality and reliable data that is relevant, accurate, complete, consistent and timely. AI algorithms must be designed and validated to ensure that they are robust, efficient, transparent, explainable and ethical.
Data privacy remains the primary concern for all. Patients are quite rightly concerned about how healthcare providers, insurers and the industry use this information. Internationally, there is an increasing adoption of the personal electronic health records whereby an individual patient will maintain a copy of their health records and choose how that information is to be shared. This may include sharing information with a clinician, pharmacist or other healthcare provider.
More personalised medicines will invariably lead to smaller production volumes and different formulations. Delivering these changes in a cost-effective manner will require innovative and sustainable solutions supported by the convergence of biotechnology with other technologies, such as artificial intelligence, nanotechnology and digital health.
As medicines become more personalised, distribution systems will need to adapt accordingly. Distribution systems will need to be adapted to consider a wide range of factors that may influence demand. This is also an area in which data analytics and AI can play a key role both in understanding the needs of the wider population, but also the environmental and seasonal factors that may impact demand levels. Such insights can be used to inform production plans and reduce the risk of future drug shortages.
It is critical that the industry is focused on future needs and expectations. Information technology and data systems can provide the biotechnology sector with powerful tools and platforms for data generation, analysis and the application of artificial intelligence solutions to develop improved insights into treatment options and enhance the efficiency, effectiveness and impact of biotechnology products and services.
Healthcare providers, regulators, manufacturers and patient groups should work together to understand the future options and put the appropriate structures in place to support the advancement of the sector, while protecting the patient.
By Claudia Carr
Claudia Carr is a partner at BearingPoint.
Updated 5.18pm, 17 April 2024: This article was amended to correct the estimated cost of adverse reactions and misuse of medications to the Irish health sector.
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