Life science analytics is fueling a transformation in the industry with its extraordinary ability to digest vast amounts of complex data. The outcome is a deeper, more complete understanding that boosts decision-making capabilities, streamlines operations, and bolsters discovery.
Moreover, it uncovers intricate patterns hidden in data and substantially enhances the return on investment (ROI) for precision medicine and clinical trials.
No doubt about it — data analytics propels the life sciences industry into a new era of insightful, data-driven, and patient-centric healthcare by optimizing processes, identifying efficiencies, and innovating solutions, and the numbers are there to show it:
- 57.1% of healthcare and life sciences organizations acknowledge data as a crucial business asset.
- 66.7% of life science companies report data as the driver behind their innovation
- 45.5% attribute data to achieving transformative business results
- Investments in AI (Artificial Intelligence) and machine learning solutions for the biopharma industry have reached an impressive $1.5B (NVP Big Data & AI Executive Survey).
- Predictions for the global life science analytics market estimate an expansion at a compound annual growth rate (CAGR) of 8.10% from 2023-2031, culminating at an impressive $18.1 billion by 2031.
In this article, we delve into the role of data analytics in life sciences and unpack the top seven benefits it offers. We’ll also offer a glimpse into the exceptional analytics services B EYE provides to help global life sciences organizations achieve their objectives.
What Is Life Science Analytics?
How Does Data Analytics Decipher Life Science Insights?
How Large is the Life Science R&D Data Analytics Market?
7 Benefits of Data Analytics in Life Science
Life Science Analytics Services at B EYE
What is Life Science Analytics?
Life science analytics can be characterized as any analytical application deployed by pharmaceutical firms, clinical research organizations, and numerous other departments, including research, marketing, pharmacovigilance, and supply chain. It involves a method of clinical data analysis that provides predictive tools for improved patient care.
How Does Data Analytics Decipher Life Science Insights?
With the world constantly searching for innovation, the ability to manipulate real-world data becomes paramount. Current trends see life science companies employing data analytics to sift through social media data, CRO, and EHR to inform their product decisions, improve existing offerings, and enhance patient outcomes. Platforms like Qlik empower companies to explore vast data sets, thus gaining insights into market demands that can be incorporated into R&D, clinical, GMA, and commercial processes.
How Large is the Life Science R&D Data Analytics Market?
A recent survey by Deloitte revealed that 91% of life sciences organizations plan to invest in R&D innovation in 2023, with nearly half expressing optimism about the sector’s prospects in the following year. However, significant financial obstacles still need to be overcome in the path of the current high-risk, high-cost R&D model’s success. That said, life sciences R&D organizations must prioritize accelerating digital transformation initiatives, strategic shifts, and commercial reorganization to navigate these challenges and thrive in a post-pandemic world.
7 Benefits of Data Analytics in Life Science
Diving headfirst into data analytics isn’t just a trendy move in today’s high-tech world; it’s a strategic leap that brings significant advantages to the life sciences sector. The impact of this data-driven revolution is vast, reshaping how we understand and navigate the industry. Let’s explore the top seven ways in which data analytics is making waves and helping life sciences evolve.
1. Enabling Personalized Medicine
Personalized or precision medicine groups patients based on genomic data, leading to more targeted treatment and superior medical outcomes. To succeed and to identify the most effective treatments for patients, vast amounts of clinical and user-generated data need to be collected, processed, and integrated. Advanced data analytics is the ideal tool for the task. It can combine data from multi-omics, EHRs, and wearable and implantable devices in real time, offering accurate analysis.
2. Enhancing Clinical Trials
Life sciences companies use technology to ensure clinical trials generate high-quality, error-free data. The goal is to expedite the drug approval process. The major hurdle, however, is managing the growing volumes of clinical trial data. Data analytics can help process large data volumes, determine relevance, and extract insights from this information. It can also leverage electronic patient hospital data and previous medical records to select the most suitable candidates for a trial, thereby saving time and improving cost efficiency.
3. Improving Risk Assessment
Risk management is a vital and non-negotiable process in the life sciences industry. Data analytics can help organizations transform risk management into a continuous process, allowing them to predict and mitigate risks before they arise.
4. Optimizing Research and Development
Data analytics can speed up data processing and derive more focused Research and Development (R&D) business outcomes. Incorporating analytics into R&D could reduce development costs by at least 15%, accelerate approval times by about six months, and significantly improve patient outcomes.
5. Assisting with Price Control, Budgeting Research, and Profit Forecasts
Life science industries now utilize big data to optimize and justify their research budgets. The data can also help them defend their profit forecasts and margins by clearly demonstrating value. Big data also enables marketers to segment prospects and customers into targeted groups according to behavior rather than merely demographics or transaction history.
6. Analyzing Remote Data
The Internet of Medical Things (IoMT), projected to reach 187.6 billion in 2028 at a CAGR of 29.5%, includes wearable, implantable, and remote health monitoring devices. Big data will be critical in analyzing the information from these devices as this market continues to expand rapidly.
7. Predicting Virus Evolution
Traditional methods discover viruses only when humans exhibit symptoms, a technique that fails to identify potentially deadly viruses that emerge due to transmission from one species to another. DNA sequencing can facilitate the discovery of new viruses by testing against extensive databases, a task for which big data is ideally suited.
Life Science Analytics FAQs
Can life sciences companies gain a competitive edge through data analytics?
Absolutely! Data analytics offers life sciences companies a significant competitive edge. It provides invaluable insights to enhance decision-making, streamline operations, and foster innovation. Companies can analyze patterns in large data sets to improve patient outcomes, accelerate drug discovery, optimize clinical trials, and predict market trends. Data analytics allows these companies to be proactive, not reactive, in an increasingly competitive industry.
How should a life sciences company implement data analytics?
Implementing data analytics in a life sciences company involves a strategic approach. First, identify your objectives: enhancing patient care, streamlining clinical trials, or boosting R&D. Next, gather relevant data and ensure it’s clean and reliable. Invest in robust analytics tools and skilled data scientists who can transform raw data into actionable insights. Promote a data-driven culture, ensuring every decision is informed by analytics. Lastly, continuously review and update your analytics strategy to keep up with evolving trends and technologies.
What factors should you consider when choosing a life science analytics partner?
Choosing a life science analytics partner involves considering several key factors. First, look for proven expertise in data analytics within the life sciences sector. The partner should have a strong track record of delivering actionable insights and results. Check their technological capabilities, including advanced analytics tools and technologies. Also, consider their commitment to data security and regulatory compliance. Lastly, ensure they understand your specific needs and can provide tailored solutions. The right partner isn’t just a vendor but an extension of your team.
Life Science Analytics Services at B EYE
With over a decade of experience, B EYE provides comprehensive Qlik analytics services to Global Life Science Organizations. Our offerings include:
- Data Analytics Consultancy
- Data Management
- Data Architecture Design
- Data Analytics Applications Development
- Data Analytics Environment Monitoring
- Extensions and Mashups
- Testing and QA
- Data Analytics Support Services
- User Training and Onboarding
- Data Analytics Team Augmentation
Explore Our Data Analytics Services
Why Choose B EYE?
At B EYE, we boast a robust team of more than 50 Qlik engineers, each possessing the skillset and expertise to stand shoulder-to-shoulder with the global leaders in the field. We don’t believe in one-size-fits-all solutions; instead, we focus on comprehending our clients’ unique business challenges and requirements. This understanding drives us to develop solutions that don’t just tick the box but add substantial business value. Our Qlik consultants are always ready to guide you toward your goals.
