With the launch of various technologies, modes of communication, apps, private-public partnerships, it seems that the pharmaceutical companies along with the healthcare industry are making efforts and thriving to find their place in this growing world. This is where digital innovations and the new trends will ease this process. It will provide collaboration and integration amid numerous parties of the companies’ network and make it easy to function. The following five trends will increasingly influence the way companies position themselves in the competitive and lucrative pharmaceutical landscape.
Vigorous Growth in the Medical Marijuana Market
The pharmaceutical and biotech companies are promising that medical cannabis drugs will become the leading opioid alternative to chronic pain treatment and will offer a range of other effective therapies. In order to identify new medical applications and innovations, researchers are increasing their emphasis on cannabinoids, the chemicals found in cannabis. In addition to pain management and other widely recognized cannabis uses, healthcare companies are also actively researching many more applications — therapies for depression, substance abuse, mental disorders, and autoimmune diseases, to name a few. Several pharmaceutical companies are joining forces instead of competing with medical marijuana manufacturers to take advantage of these potential new markets to generate revenue.
With the industry booming as U.S. and many other nations and states legalize medical marijuana use every year, many business sectors are expanding into the pharma-dominated area for cash-in medical research. Even beverage king Coca-Cola is exploring a deal with Canadian cannabis manufacturer Aurora Cannabis to create a cannabidiol-infused “wellness drink”. Given the hype of medical marijuana taking pharmaceutical companies — and their investors — by surprise, the conclusive health effects of marijuana are still lacking in factual evidence.
Continued spreading and increase of Cloud Technology
The pharma sector was one of the last to fully embrace cloud computing technologies due to the sensitive nature of the large amounts of data handled and processed by pharmaceutical companies. Pharmaceutical companies hesitated, citing concerns about data security and compliance as prohibitive reasons for avoiding the use of external networks to access resources. The cloud change had started in science and drug development laboratories and continues to pave the way. The spark was ignited once the broader industry began to notice the efficiencies achieved by research institutions introducing cloud computing services. While drug companies have learned over the past few years that the benefits of switching to the cloud greatly outweigh the risk, the floodgates are now wide open.
Plentiful Uses of AI Beyond Drug Discovery
Artificial Intelligence (AI) has developed itself as a cost-effective tool to help pharmaceutical companies keep pace with changes in the standard of care for the healthcare industry. But while start-ups from drug companies and global mega corporations continue to jump on the AI-as-drug-discovery-tool train, a wide plethora of new and useful AI applications are emerging trends in pharmaceutical environments. A growing number of drug developers show that AI can be utilized by automating and streamlining processes, making better data-driven decisions, and developing smarter analytics tools to improve R&D performance. In order to facilitate these ambitions, enterprising pharmaceutical companies of all sizes follow the lead of tech giants such as Google and Intel by promoting “intrapreneurship” to promote creativity and develop in-house realistic AI tools. Internal technology laboratories such as Siemens ‘ Intrapreneurs Bootcamp AI and open science projects such as the QuickFire Challenges provided by Johnson & Johnson Inventions Lab allow pharmacists with a passion for AI to tinker with their company time ideas in the hope of encouraging product inventions to grow.
Some of the developing AI advancements that are expected to pique the pharma world’s interest this year include:
- Data preprocessing and analytics applications that integrate different types of biomedical and health care data with existing business processes.
- Patient diagnosis tools and clinical judgment aids.
- Applications for drug repurposing and predicting the pharmacologic properties of drugs.
- Applications for pattern recognition in personal genetics and diagnostic tools for genetic research and DNA interpretation.
- Disease identification and management applications.
- Potential drug delivery mechanisms.
- Applications for precision medicine and hyper-targeted drugs.
- AI-assisted robotic surgery.
- Virtual nursing assistants.
- Tools designed to mine data for scientific discovery.
- Prosperous business-academia partnerships.Automated matching of drug interventions with individual patients to predict drug treatment results.
AI will generate 500,000 more jobs worldwide and would see constantly growing demand for jobs throughout 2019 throughout the healthcare sector.
Increasing Adoption of Predictive Analytics and Machine Learning Systems
Previously considered a costly gamble, pharmaceutical companies are rapidly embracing smart predictive models and ML as reliable methods to evaluate patterns and trends and effectively contextualize data.Pharma organizations are increasingly using predictive analytics and ML technologies for:
- One of the most exciting fields where the industry explores future ML applications is precision medicine, which aims to offer new pharmacological treatments by reframing diseases in ways that both recognize pathological and physiological mechanisms.
- Several pharmaceutical companies are beginning to mimic the specialization strategies of leading ML developers such as IBM Watson Oncology, who are applying predictive analytics to patient knowledge and experience to improve care decisions. These types of programs are expected to open up lucrative niche markets.
- Even in its beginning — from Amazon’s new software that scans patient records to provide health care providers with treatment-improving knowledge to Google’s DeepMind Health initiatives that incorporates algorithms to identify issues in eye scans and mammograms — ML is already showing promise as a primary driver of superior patient care.
- Pharmaceutical companies are hoping that these forms of machine learning systems will potentially lead to better approaches for drug design and patient data collection.
- Advanced data analysis will boost efficiencies, planning activities and management of the supply chain across an organization.
- ML could also function as a way to measure the effect of individual teams on medicine and the market (which would be particularly beneficial for medical groups and related subgroups), thus strengthening collaboration between science, medical and marketing workers.
Pharma companies and health care providers alike are hoping that predictive analytics and ML tools lead to better insights that will improve pharmaceutical products and patients’ quality of life.
Intensified Regulatory Focus on Data Privacy Issues
As quantitative data science is more frequently used to fuel pharmaceutical successes, regulators’ concerns about data privacy and management issues are intensifying. Pharma professionals are continually facing expectations to do more with the data they have at their disposal. They will be required to cope with proportionately constrained compliance efforts as new data management regulations are added and enforced in coming years. In addition, they’ll need to devise inventive tactics for overcoming institutional roadblocks if they hope to gain organizational buy-in for new data management ideas and strategies.
