Call Us Today! (732) 701-7807|info@ozmosi.com
facebooktwitterlinkedin

Data Analytics

DIABETES PIPELINE ANALYSIS – MERCK

2017-08-28T20:39:22+00:00

Merck’s two blockbuster diabetes products, Janumet® and Januvia®, are DPP-4 inhibitors that generated nearly $3.3 billion in Sales in 2016.3 Januvia® is especially known for its great cardiovascular safety profile, which has helped differentiate itself in its class. But Merck has no plans of stopping there with four different products in late stage development that appear to be promising. In conjunction with Pfizer, the company recently filed NDAs for three SGLT-2 inhibitors based on their  ertugliflozin molecule – one as a monotherapy, another in combination with Januvia® (sitagliptin) and the third a combination with metformin. Despite expectations to launch with three [...]

DIABETES PIPELINE ANALYSIS – MERCK2017-08-28T20:39:22+00:00

Letting the Data Tell the Story

2017-08-03T17:10:10+00:00

In our previous post we described the technique for assigning categories to data, based on input from content experts within a “training database”.  This technique is effective for summarizing large, text-heavy data into specific categories for summaries and improved visualization.  While this approach is useful for those purposes, it will not allow us to uncover new insights or trends because we are imposing a preconceived and finite set of options, or in other words, what we already know. The following describes our approach to using clustering techniques for exploring text-heavy data. We applied this technique to two different datasets: scientific journals [...]

Letting the Data Tell the Story2017-08-03T17:10:10+00:00

USING NLP TECHNIQUES TO CLASSIFY PATIENT SEGMENTS IN CLINICAL TRIAL DATA

2017-08-02T19:24:26+00:00

One of the most common and powerful approaches in NLP provides the content experts an opportunity to label each data segment for a portion of the dataset and then analyze these labels to apply to the rest of the dataset. Some key questions need to be answered when applying this approach in different environments.   For example, how many “expert” labels do we need to create before the classification works effectively?  How can we evaluate this in advance?  Are we limiting ourselves to only extracting from the data what we already believe to be true?  We will discuss that last one in [...]

USING NLP TECHNIQUES TO CLASSIFY PATIENT SEGMENTS IN CLINICAL TRIAL DATA2017-08-02T19:24:26+00:00

Finding the Needle in the Haystack with NLP

2017-07-18T20:11:29+00:00

The problem with Big Data is that it is so Big!  This issue is especially true in the world of healthcare and drug development.  It is difficult to see across all the good clinical/scientific work going on around the world and understand exactly where we are headed and how we will get there for any given disease area.  It’s about time we move from manually tackling the pharmaceutical data to using the power of natural language processing (NLP) and machine learning.  NLP is at its early stage in the pharma industry and brings a strong potential to find trends and insights [...]

Finding the Needle in the Haystack with NLP2017-07-18T20:11:29+00:00