In the post-COVID-19 era, now more than ever, patients are critical of the healthcare they receive. Yaron Gissin, Chief Innovation Officer of the Sade Group, explores the benefits of individually personalised medicine via digital data and tools.
Traditionally, the world of medicine has relied on clinical guidelines based on the results of large randomised controlled clinical trials (RCTs) and meta-analyses that, in theory, are applicable to the average patient. Nonetheless, doctors do not treat ‘average’ patients; thus, the use of this generalised knowledge within the field of medicine could prevent the individual patient from receiving the best possible personalised care.
The COVID-19 pandemic has prompted widespread use of real-world data1. Desperate for medical insights without delay, researchers, pharmaceutical companies and government agencies turned to health information captured through real-world data sources. By analysing COVID-19 datasets, the research community rapidly helped fill in knowledge gaps. When it comes to medical cannabis, despite growing legalisation, popularity and an ever-increasing demand, standardisation is still in its infancy. Isn’t it time to leverage the advances in big data and AI to garner real-world data that may finally provide the much-needed evidence to manage individual patients?
Modern medicine: standardisation versus individualisation
Modern medicine and healthcare encompass two contradictory trends, standardisation and individualisation. The essence of individualised medicine is that the individual patients should receive medications appropriate to their clinical needs, genetic profile, environment and lifestyle, in order to optimise the benefit and minimise the harm. Clearly, personalised medicine is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.
The healthcare industry is placed with the challenging task of converging the efficiencies and quality of standardisation, with patients’ preferences and precision medicine enabled by emerging technology and big data analytics.
Transforming data into knowledge for personalised treatments
We live in the era of big data. According to The Economist, it is not oil but rather data that represent the key resources of the 21st century2.
Advances in technology, data science and healthcare policies have resulted in tremendous growth in the volume, sources, and utilisation of health data and real-world evidence. Furthermore, the expansion in the use of electronic health records, IoT, wearables, and mobile applications generate constant data streams that can be utilised endlessly thanks to methodological advancements such as machine learning, AI and natural language processing.
The healthcare workforce has massive amounts of patient and disease-related data at its disposal. This presents an urgent need to develop new, scalable, and expandable big data infrastructure and analytical methods that can enable healthcare providers access knowledge to deliver personalised medicine and care for the individual patient, yielding better decisions and outcomes.
Medical cannabis in the era of personalised medicine
Medical cannabis is a unique example in medicine where:
- Many patients seek out medical cannabis treatment, yet, for many physicians, the ability to prescribe feels like a ‘leap in the dark’ – such a mismatch between demand and supply is rare in medicine;
- A new medication is introduced to the market via legislation rather than through formal drug development practices3; and
- We see a reversal of the trend towards single molecule drug development in favour of the use of raw botanical products containing complex chemovars.
Cannabis offers significant therapeutic benefits for a wide range of conditions – including cancer, chronic pain, Alzheimer’s disease, depression, epilepsy, multiple sclerosis and more – without substantial risks or unmanageable side effects4.
As the list of diseases and symptoms in which cannabis shows therapeutic effects constantly grows, the focus should clearly shift from whether cannabis has any therapeutic value, to the development of digital tools and efforts that may optimise medical cannabis treatment.
Raw herbal cannabis cannot be regulated in the same way as single-molecule pharmaceutical medicines. Cannabis contains at least 600 individual compounds, including cannabinoids, terpenes, and flavonoids, all of which work together in synergy to create ‘the entourage effect’ (Ethan B Russo, 2018).
Additionally, the complexity of cannabinoid pathways, as well as the ‘individual genetic predispositions’ that modulate how different individuals process cannabinoids, ultimately lead to a wide variety of different ‘body responses’ to cannabinoid therapy5.
Medical cannabis is the antithesis of the modern one-size-fits-all pharmacopoeia of single-molecule drugs used in medicine today. To realise its therapeutic potential, a different approach is warranted.
Enhancing evidence generation to optimise personalised treatment
Over the past five years, Sade Group has continuously investigated the pain of patients as well as the pain points of the industry: lack of clinical evidence, lack of research, a plethora of products lacking clarity about what works and what does not, lack of collaboration between required fields of speciality.
Our vast experience and unique expertise in both medical cannabis genetics, cultivation and big data analytics have matured to the understanding that in order to advance medical cannabis precision care, a multidisciplinary approach is required; one that involves the entire spectrum of this industry – patients, healthcare professionals, researchers, data scientists and growers. Such integration of multiple sources of data, knowledge and experience is crucial to finally enable medical decisions specific to the individual characteristics of patients.
We decided to lead and be in the eye of the storm of this tectonic shift: from personalised healthcare, through real-world, evidence-based medicine, to the use of machine learning aimed at extracting important knowledge from masses of data.
Building data integration and analytical platforms can help synthesise fragmented data into comprehensive analysis, providing instant, on-demand best practices.
The ASAYA™ solution
ASAYA is a unique, big data platform that integrates real-world practice and patients’ reported outcomes, with human and machine intelligence, to provide practical guidance for the use of medical cannabis. Facilitated by cutting edge technology – machine learning, IoT, mobile applications and predictive analytics – ASAYA captures clinical data directly from HCPs, patients, researchers and growers to generate the evidence sorely needed to optimise medical cannabis care.
Key features designed to achieve breakthrough performance:
- ASAYA is constantly fed with new data, from the entire ecosystem of medical cannabis – clinicians, patients, local producers, researchers, and industry stakeholders;
- ASAYA’s HCPs Dashboard provides instant access to comprehensive data in real time, while transforming extensive heterogeneous data into scalable, medically actionable resources; and
- The ASAYA patient mobile app: a free easy-to-use patient app that provides access to an HCP directory, a global knowledge centre, a treatment reminder, a medication tracker and is integrated with a customer care telemedicine call centre manned with medical staff.
The ongoing accumulation of data from physicians and thousands of patients already onboarded in the ASAYA big data platform is about to create a more solid, yet personalised and accessible, set of best practices in medicine that will enable medical cannabis care with confidence.
In the past year ASAYA has rapidly deployed and skilfully managed for commercial and clinical usage with thousands of patients. Collective wisdom optimised by advanced technology holds great promise to improve individual care. Our first and foremost commitment is to people around the world suffering from debilitating symptoms and diseases.
ASAYA is built and constantly refined to enable practitioners to make better decisions for the individual and better decisions for society. Our mission and end goal are to contribute to a health system that is driven by evidence and based on value, for the benefit of people.
1 Dolgin E. The pandemic is prompting widespread use and misuse of real-world data. PNAS Nov 2020; vol. 117(45)
2 Leader, The Economist. The world’s most valuable resource is no longer oil, but data. 6 May 2017.
3 Bonn-Miller M et al. Cannabis and cannabinoid drug development: evaluating botanical versus single molecule approaches. Int Rev Psychiatry. 2018 Jun; 30(3): 277–284.
4 Reynolds P. Feb 2015. Medicinal cannabis: the evidence. CLEAR Cannabis Law Reform.
5 Hryhorowicz S, Walczak M, Zakerska-Banaszak O, Słomski R, Skrzypczak-Zielin´ska M. Pharmacogenetics of Cannabinoids. Eur. J. Drug Metab. Pharmacokinet. 43, 1–12 (2018).