“Our world is increasingly complex, often chaotic, and always fast-flowing. This makes forecasting something between tremendously difficult and actually impossible, with a strong shift toward the latter as timescales get longer.” ― Andrew McAfee
Accuracy of forecasting and analysis in the pharmaceutical industry depends on the data quality. Epidemiological data robustness is the key to making high-quality predictions. Today many factors affect forecasting, starting from new emerging technologies and ending with completely new approaches to disease treatment/prevention. That’s why a pharmaceutical company should closely focus on using the most precise epidemiological data for an accurate analysis.
Here are four important types of epidemiological data you should pay attention to when determining a product development strategy:
1. The Number of Patients Suffering From The Illness
In order to estimate the potential of a certain drug, you need to evaluate the target market. The number of people suffering from a certain illness is the simplest way to get an idea of how well your drug may do in a particular country. While you can base this on the data available as a result of certain studies, you need a high-quality database to get reliable results.
Black Swan uses its unique Epiomic database, which covers a variety of countries and diseases. Access to this database is available to subscribers.
2. Treatment Patterns
Learning how the patients are prescribed and consume medications can help strengthen a forecast for a certain drug. Which patients are prescribed which drugs? Are there key segments of populations more likely to receive a specific drug than other segments? Which segments would be contra-indicated from receiving your medication? This type of epidemiological data is often available in the form of statistics. However, it rarely encompasses all the patients in one country.
With the assistance of the Epiomic database and access to a variety of studies and national sources, we can help identify clinically relevant patient segments in European countries and beyond.
3. Patterns Of Disease Development
Studying certain patterns of each disease can help you find out when the drugs you manufacture are needed the most. For example, the seasonal appearance of flu is directly related to the manufacturing of the vaccine. Different countries may have different disease patterns. This epidemiological data is not always readily available for each country. In fact, some resources are updated so slowly that they become useless for short term forecasting needs.
At Black Swan Analysis we use rigorous research algorithms for epidemiological data collection. The data relevance is scrutinised to extract the most useful information for analysis and forecasting.
4. Epidemiological Studies
Epidemiological studies are a great source of epidemiological information coupled with a relevant analysis. They provide the best patient and market estimates over the mid to long term. Analysing multiple studies to single out the necessary data types may be complicated. Once extracted, the information can become a priceless tool for drawing up the right forecast.
Our team has over a decade of experience dealing with extracting the necessary epidemiological data from global medical studies and processing the information to make it as useful as possible for the company’s needs.
Epidemiological data collection is a complicated and a time-consuming process. Leaving it up to the experts can save a substantial amount of time and money. To find out more about how we can help, please send an email to firstname.lastname@example.org.