D I S S E C T I N G B U S I N E S S
leukemia to be at 90 % compared with 35 % for conventional chemotherapy .
A European Commission study discusses a ‘ DNA medication pass ’ developed by researchers to capture a patient ’ s unique genetic identification markers . Clinicians can scan the pass to identify the best-suited medication for a specific patient with 30 % fewer side effects from the precision drug they then prescribe .
With advancements in data science-based tools , AI , and ML , raw data is converted to timely insights to determine what works best for a specific profile of patients . Methods that have become established , like genome sequencing , biomarker testing etc ., rely on AI / ML models that match biomarker patterns and make relevant inferences on how a disease is progressing for a specific patient .
Digital twins
Subhro Malik , Senior Vice President and Head Life Science , Infosys
Personalisation of care powered by technology
Technological advances such as the availability of massive computing power , data analytics tools , and sensors have enabled several innovations in personalised healthcare :
Predictive analytics and AI / ML
With preventive care increasingly becoming a priority , genetic testing is an important area of focus . Individuals found to be at a greater predisposition to illnesses such as breast cancer and Alzheimer ’ s can receive a preventive care plan to ensure a better quality of life .
Discarding the conventional trial-and-error method , they can cut down the probability of adverse effects of medication by finding a treatment plan that befits the individual ’ s genetic profile .
A digital twin ( data model ) of each patient can be generated to accelerate drug development while giving an affordable option for those conducting a pre-trial before the one involving real participants and more investment . AstraZeneca is using digital twin modelling along with in-silico experimentation and simulation to accelerate development lead times and reduce waste . The additional benefit is that any medical intervention can be specifically developed and designed around those actually requiring it .
Computing power and analytics capabilities
Digital platforms make it possible to store data with fast , easy and anytime-anywhere access , which in turn speeds up decisions for healthcare providers . This can be valuable in complex activities such as genome sequencing that require huge amounts of data .
The scalable , flexible solutions and massive computing power enabled by cloud-based infrastructure help store and access the right data at the right time . This data is accumulated and analysed across people of different origins , environmental conditions and lifestyles . It is then possible to extrapolate and identify the precise treatment , develop target medical interventions , trace their impact and take corrective action where required .
Several factors inhibit technology adoption
Despite the clear advantages , technology adoption in life sciences has been sluggish . A paper by the European Parliament found that breakthroughs in personalised medicine coming through into standard clinical practice were fewer than expected .
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