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Precision medicine spend to exceed $132bn globally by 2027

A new study from Juniper Research found that the total spend on precision medicine will reach $132.3bn globally by 2027; increasing from only $35.7bn in 2022.
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This strong growth of 270% is a result of emerging technologies and infrastructure, such as AI, which aids precision medicine by predicting risks for certain diseases.

These technological advancements, combined with the healthcare sector’s need to increase efficiencies in the face of an economic downturn, will encourage healthcare providers to invest further into precision medicine.

Precision medicine leverages advances in personal genomics to enable healthcare providers to prepare preventative plans and disease treatments based on gene variability.

Cost savings and better outcomes drive growth

The research predicts that benefits such as reductions in adverse reactions from ineffective medication, improving the efficacy of treatment plans by means of personalisation, and cutting patient spend on medication, will be the primary drivers of precision medicine adoption among healthcare providers.

To maximise these benefits, the report identified the use of AI to ingest and process large amounts of healthcare data to increase the future accuracy of diagnoses.

Research author, Cara Malone remarked: “The rapid increase in accuracy, as systems become more advanced, will create a virtuous cycle of continuous improvement; catalysing further growth and adoption of precision medicine in healthcare sectors over the next five years.”

Genetic predispositions vs healthcare premiums

The research anticipates that the most significant issue surrounding precision medicine will arise from patient data privacy concerns.

In many countries, but predominantly the US, there are fears that uncovering genetic predispositions using precision medicine will lead to insurance providers leveraging these insights to increase healthcare premiums.

To allay these concerns, vendors must consider voluntarily adopting strong codes of conduct around data privacy, as well as creating independent advisory councils, to reassure users and limit the scope of data sharing.

Read more: data, AI, precision medicine

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