Considering the current world events, the pharmaceutical industry is in the midst of unprecedented change. It is more important than ever for pharma companies to improve their scalability, efficiency and speed to market. They have to keep up with the health needs of patients while maintaining stringent regulations and compliance standards.
The industry is up against a fresh set of challenges, and the pandemic has spurred the adoption of innovative technologies to support its various functions. The priorities of pharma companies include strengthening R&D, achieving global market growth, and adopting digital and IT transformation. Some of the key challenges faced by the industry include adapting to changing consumer behaviour and accelerated technology advances, while also coping with cyber threats and dealing with complex data from various sources.
How Technology is Aiding the Pharma Market
Bringing a drug to market is usually a costly and time-consuming process. Pharma companies are constantly under pressure to report to governments, regulators and consumers on drug safety and efficiency. They need to be transparent, innovative, and accountable in their drug-development process. In order to focus on modernizing the drug-development processes, pharma companies need to automate some of their time-consuming tasks.
Cutting edge technologies such as AI and deep learning aid the pharma industry by improving the clinical trial design, new drug development, R&D activities and other day-to-day operations. Natural Language Generation- an advanced AI technology can make a huge difference to the pharmaceutical industry. The technology automatically converts structured data in the form of tables, charts, and graphs into descriptive reports in plain natural language. It can analyze the data and generate error-free reports from it at a much faster pace.
NLG can help pharma businesses by simplifying data preparation and analysis, amplifying the speed of data submission, nullifying errors in reporting, and improving inventory management. It automates clinical safety report generation and accelerates the drug development and delivery processes. Natural Language Generation in pharma can also save a lot of time, effort, and money of pharmaceutical industry professionals by handling bulky-data work and freeing them up to focus on other productive and higher-value work.
The Role of NLG in Pharma
1. Writing Automated Clinical Study Reports (CSR)
The most critical phase for pharma companies in bringing a drug to the market is the human drug trial. Writing Clinical Study Reports (CSRs) that describe the impacts and trial outcomes of the drug is a challenging part for the clinicians. It requires medical writing teams to manually create reports out of the data collected from the human drug trial, which is a time-consuming and tedious process.
Automated content generation software powered by AI can help pharmaceutical companies to accelerate the speed of generating Clinical Study Reports (CSRs) by more than 40%. Driven by NLG, it connects to the clinical study database and automatically generates reports that meet regulatory requirements. Content automation results in faster time-to-market for life-saving medications, leading to better public health.
2. Monitoring Medical Representative Performance
The performance of medical representatives is one of the key driving forces for pharma sales performance. The MRs meet and talk to various doctors and drug distributors to expand their distribution channels and sales. Their performance is usually measured by tracking the average calls they make, the number of meetings they attend, the number of doctors and drug stockists they visit, etc. By tracking and analyzing these metrics better, pharma companies can gain insights on the performance of their medical representatives and take necessary actions to improve sales.
Businesses usually have ERPs and analytical tools in place that help them analyze these metrics. However, these tools offer insights from the data in the form of complex spreadsheets that are difficult to interpret. Advanced automated report writing tools that use AI and natural language generation to convert complex spreadsheets and data into reports written in plain natural language can be used by pharma companies to easily monitor MR performances and get quick actionable insights. These medical representative reports can be used by the med reps to evaluate their performance and take necessary actions to improve the overall sales of the company.
3. Exploring IMS Data for Strategic Decision-making
In order to track the overall performance of the company and to make informed decisions, pharma companies also use market data gathered from various sources of the industry. While there is plenty of data available in IMS databases, extracting the necessary and useful insights from it can be a challenging task. Artificial Intelligence report writing is helping pharma companies to make the most out of their IMS health data analysis with the help of NLG.
NLG-based automated reporting software translates data in the form of charts, graphs and tables into trends presented in easy-to-understand language. It highlights the key patterns and trends and aids the company in making performance-enhancing decisions. By using these trends, pharma companies can get in-depth insights about their best and worst-performing brands and products, overall market share and statistics, and make decisions that can lead to improved business results.
4. Curating Regulatory Documents
The R&D and patent process in the pharmaceutical industry is a tedious and time-taking one. There are huge chunks of data that need to be analyzed at the pre-clinical, clinical and commercialization stages of the process, which is prone to human errors and blunders. Regulatory documents require utmost precision, since any blunder may directly affect the time to market of the drug. NLG makes curating regulatory documents easier and less prone to errors. It reduces redundancy and information duplication while ensuring improved data quality and information security.
5. Communicating in Multiple Languages
Pharma and healthcare professionals do not have the time to create detailed reports and documents for each patient. They provide information in the form of graphs and tables. NLG has the ability to study information and produce documents in multiple languages. It analyzes the clinical study database and generates multilingual auditable documents instantly, which can be used by pharma professionals to effectively communicate with the patients. It enables pharmaceutical companies to create personalized reports and documents to meet individual patient requirements.
Revamp your Pharma Processes with Phrazor’s Data-Driven Storytelling
Automation and augmented analytics are transforming the pharma industry by increasing the efficiency of clinical trials, accelerating drug development, improving sales and marketing efforts, and streamlining compliance. Phrazor is an augmented analytics tool that uses NLG and data-driven storytelling to help pharma companies to get detailed insights from their pharma data and improve the efficiency of pharma reporting. It provides granular insights on key industry trends and metrics to help pharma companies make smarter business decisions, reduce costs and improve revenue. With automated reporting, it streamlines compliance while significantly reducing the possibility of human errors.
If you are a pharma company looking to improve performance reporting and business intelligence to drive better sales and performance, Phrazor can help. We have assisted leading pharma and healthcare enterprises in improving the productivity and effectiveness of their processes with augmented analytics and reporting automation. Our tool saves a lot of time and effort of pharma professionals by allowing them to get detailed insights from their data in just a few clicks.
Get in touch with our pharma experts today to explore more.
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.