Interesting times are ahead as Pharma 5.0 marketing is revolutionizing the traditional oncology marketing strategy. To disrupt the whole ecosystem, the return on investment/engagement cannot liaise solely within R&D. Notably, the return investment is not only distinguishable across, for instance, commercial subsectors, but also seamlessly quantifiable. Hence, enterprises can expect a significant profit margin at the end of the tunnel of a long-term investment strategy. Thus, with time, it results in a more patient-centric ecosystem with more success rates and star products.
With time, digital health tools are navigating the way toward more patient-centricity in the oncology market. Although Pharma 5.0 is on the brink, it has showcased its potential for early intervention in cancer care by investigating patient data from EHRs, imaging machinery tests, and online platforms. Simultaneously, precision medicine is taking center stage as advanced digital health tools incorporate more genetic and molecular data into their systems. Hence, focused treatment has never been more intriguing to caregivers while offering them more work-life balance.
Moreover, digital health allows remote monitoring which is a boon for caregivers as they need to keep a periodic update of their patients. Latest gadgets like wearable devices (smartwatches/bands etc.) and telemedicine allow continuous health tracking, minimizing the necessity for chronic hospital visits. These devices generate huge sets of patient data that leverage clinical trials and R&D. These goldmine of datasets fuels oncologists’ understanding of cancer biology, treatment factors, and the overall development of novel therapies. With the inclusion of digital health in oncology marketing strategy and respective R&D, patient-centricity can be achieved at the most optimum and ethical level.
Classifications of Digital Health Applications in Oncology
- Screening and Diagnostics
This topic definitely calls for a discussion regarding genomic sequencing as it involves the holistic analysis of a patient’s genetic structure, providing crucial insights into genetic mutations and nuances associated with prognosis, cancer risk, and treatment response. By decrypting the patient’s particular genetic profile, oncologists can customize treatment plans to target particular genetic anomalies. Genomic sequencing is enhancing the potential of precision medicine, allowing for the administration of focused therapies that cater to the underlying genetic drivers of cancer. Additionally, it assists in accessing cancer vulnerability, allowing early interventions and insurance for patients at higher genetic risk.
Liquid biopsies on the other hand also assist caregivers in identifying the exact biomarkers (circulating tumor cells) in patients, in no time. Along with early detection, these also offer a comprehensive view of the patient’s status.
Advanced image analysis in oncology diagnostics has been trending since Industry 4.0. Radiomics complements the fast-paced industry trends by extracting quantitative data from MRIs and CT scans. Ultimately, it is accelerating the diagnostic timeframes by providing accurate and prompt tumor insights to oncologists and respective HCPs.
- Decision-making Support Systems
The inclusion of AI/ML algorithms in digital health platforms is the exact collaboration that every HCP wants in the oncology ecosystem. These tools integrate huge data sets, including medical literature, patient data, and clinical guidelines to help HCPs in making personalized treatment prompter and more seamless. For oncologists, intensive inclusion of AI helps modify therapy through the easy accessibility of key information like genetics, comorbidities, disease stage, and treatment history.
With big data, drug discovery has never been more seamless, where AI can predict drug interactions and adverse effects. This leads to the ethical and safer development of novel cancer therapies and drugs.
- Remote Monitoring
This advancement has already been discussed earlier but their significance towards monitoring heart rate, oxygen, and blood pressure levels is noteworthy. With the liberty to monitor the vital signs of patients remotely, oncologists find it easy to early detect complicacies with real-time data.
With the advent of Pharma 4.0, virtual care platforms and telemedicine are the lifelines of the oncology marketing strategy of any pharma enterprise. And more of them should be embracing the same as they offer mental health support, consultations with oncologists, and follow-up appointments. Moreover, patients don’t have to worry about their privacy as these platforms have leveled their game pretty high in data encryption, thus removing the need for in-person visits. They are life savers for patients who have compromised immune systems post-chemotherapy. Apart from providing prompt medical advice, they are the leading tools for personalized care where there are zero infectious risks.
- Patient Engagement and Holistic Support
There happens to be a plethora of mobile applications (CareZone, Cancer.Net mobile, BELONG, etc.) and end-user portals, encouraging patient engagement with holistic support systems. These new-age apps with smart algorithms offer patients with- knowledgeable contents, symptom tabs, medication prompts, and also effective communication with caregivers.
As the industry speaks more about patient-centric oncology therapies, empathy has been bolstered from lab to market. Digital health also gave an empathetic touch by extending its boundaries toward supportive care services. This involves palliative care resources counseling services and online group support. Moreover, they cater to the emotional, social, and psychological perspectives of patients and not only the medical aspects of it.
- Governing Data & Analytics
Over the years, EHRs have gone through several challenges in digital health and ultimately ended up- disrupting the volatile oncology market. And why not, when it’s the real-time resource of oncology-driven data?
However, enterprises should be implementing them more with machine learning techniques to come up with applications that lead to predictive analysis, prognosis, and outcomes. Advanced machine learning models can also streamline provider interactions with EHRs through speech recognition and minimizing data entry through natural language processing (NLP).
With the help of big data and ML tools, any oncology marketing strategy can be made robust but has to overcome some challenges- (a) Bad data quality can be fought with quality research in biospecimens (b) Unstructured databases need to be streamlined and (c) Insufficient analytics and lack of delivery needs to be met with trained technical computational personnel, who would train the relevant algorithms.
Future trends include-
- Inclusion of more AI/ML algorithms in drug discovery towards delivering personalized treatment.
- Integration of AR/VR to revolutionize oncology education directed toward patients and their respective families.
- Predictive analytics and early intervention will experience a surge of demands from all stakeholders of the oncology industry.
- More expectations of predictive analysis will lead to more global collaborations and data sharing.
- Interoperability mandates are expected to be more emphasized by policymakers. On the other end, an adaptive regulation framework to be more practiced with digital health platforms continues to build trust with data encryption.
It is evident that the landscape of digital health in oncology will continue to tilt towards offering more focused therapies. However, enterprises must abide by ethical practices and compliance norms towards optimal usage of datasets relative to this industry. Teamwork among varied HCPs, decision-makers, and researchers is the key to unlocking the full potential of digital health, while the pharma oncology market awaits more innovative strategies.
