Fast Data Science

BACKGROUND

Please describe your company and position.

 I am the Deputy Director of a non-profit company 

Describe what your company does in a single sentence.

Non-profit foundation funding Global Health research and Global Development.

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire Fast Data Science to accomplish?

• Engage in AI tool product support and ongoing enhancement of the AI tool (from V1.0 TB and HIV coverage to subsequent versions supporting trial protocol reviews for research in other diseases).
• Develop a browser-based tool which uses AI and natural language processing to identify and quantify the risk of clinical trial uninformativeness.
• Quantitatively measure the accuracy of the AI tool by comparing the tool's classification of trial protocols (trials whose results are already known).
• Create software requirements specifications (SRS), design document, and end-user documentation for the AI uninformativeness risk classification tool.
• Author scholarly manuscript describing the AI tool and achieve publication of the manuscript in a refereed journal.
• Create instructional videos for training of clinical trial reviwer end-users in the use of the AI tool.

SOLUTION

How did you find Fast Data Science?

Referral

Why did you select Fast Data Science over others?

• High ratings
• Great culture fit
• Good value for cost
• Referred to me

How many teammates from Fast Data Science were assigned to this project?

1 Employee

Describe the scope of work in detail. Please include a summary of key deliverables.

Develop a browser-based tool which uses AI and natural language processing to identify and quantify the risk of clinical trial uninformativeness. The tool reads and parses the text of trial protocols and identifies key features of the trial design, which are fed into a risk model. The application runs in a browser and features a graphical user interface that allows a user to drag and drop the PDF of the trial protocol and visualize the risk indicators and their locations in the text. The user can correct inaccuracies in the tool’s parsing of the text. The tool outputs a PDF report listing the key features extracted. V1.0 of the tool is focused HIV and tuberculosis trials and was subsequently extended to more pathologies in future. Results: On a manually tagged dataset of 300 protocols, the tool was able to identify the condition of a trial with 100% area under curve (AUC), presence or absence of statistical analysis plan with 87% AUC, presence or absence of effect estimate with 95% AUC, number of subjects with 69% accuracy, and simulation with 98% AUC.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

Excellent accuracy in predicting clinical trial protocol risk of noninformativeness. On a manually tagged dataset of 300 protocols, the tool was able to identify the condition of a trial with 100% area under curve (AUC), presence or absence of statistical analysis plan with 87% AUC, presence or absence of effect estimate with 95% AUC, number of subjects with 69% accuracy, and simulation with 98% AUC. Manuscript was published.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

They met all deadlines on time and on budget. All deliverables were of high quality. Responses to the original scope-of-work brief and subsequent enhancement requrests were top-notch. Bravo! Would engage Fast Data Science and Thomas Wood again!

What was your primary form of communication with Fast Data Science?

Virtual Meeting

What did you find most impressive or unique about this company?

Careful design, capable engineering, excellent software QA, comprehensive documentation and training, cheerful responses to difficult problems.

Are there any areas for improvement or something Fast Data Science could have done differently?

No areas for improvement arose during the engagement. Superb Fast Data Science performance on this AI development engagement.

BACKGROUND

Please describe your company and your position there.

Through its vast network of National Alliances, our nonprofit is activating the global movement for reproductive, maternal and newborn health and rights.

I work as the Senior Communications Officer, working closely on the "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign that heard from more than 1 million women and girls in 114 countries about the one thing they want most for their own reproductive and maternal healthcare through an open-ended survey.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Fast Data Science?

The "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign resulted in the collection of nearly 1.2 million open-ended survey responses from women and girls around the world, in 18 languages.

Fast Data Science helped us analyze the requests to help us create advocacy agendas around those requests; these advocacy agendas are currently being used to elevate the voices and demands of women to create policy change. Fast Data Science used NLP and machine learning to analyze the survey responses, and to create an interactive dashboard for advocates interested in examining the data.

What were your goals for this project?

We wanted to understand the data we had in our hands, and be able to examine it and use it in a way that would allow our group to elevate the demands of nearly 1.2 million women around the world.

SOLUTION

How did you select Fast Data Science?

Fast Data Science had all the qualities we were looking for in our large data project - in-depth understanding of the technology needed to achieve our goals, as well as excellent staff capable of explaining the complex technical aspects of the work in a way that our entire team could understand. And, as the name implies, Fast Data Science was extremely fast, helping us meet our deadlines.

Describe the project in detail.

After connecting with Fast Data Science, we held an initial kickoff conversation where the complexities of our project were laid out. We then shared all of the data and work that we had done on the project with Fast Data Science to run their analysis and begin the work.

Within one month, which included several conversations and refining of our requests as our side understood the power of the technology available to us, we had an our data not only analyzed but shared back with our team in plain language and in clear infographics.

We then began a new phase of the project where Fast Data Science converted our massive amount of static data into an interactive dashboard using Python and other tools.

What was the team composition?

I worked most closely with the Data Science Team, with others from my organization's side joining in on phone calls and planning sessions.

RESULTS & FEEDBACK

Can you share any outcomes from the project that demonstrate progress or success?

Fast Data Science helped us analyze nearly 1.2 million open-ended survey responses, allowing us to clearly see what our data was saying, and is now helping us present that information for an external audience with an interactive online dashboard that will allow users to perform their own deep dives into our data.

This dashboard was a dream project that we were not sure was actually possible to create - Fast Data Science helped us realize this dream and we are very pleased with the work.

How effective was the workflow between your team and theirs?

Fast Data Science was extremely responsive, and available for calls, sharing of information, and even presentations with our global team on a regular basis. We communicated over email and through Zoom, and our communications were always efficient, informative, and enjoyable.

What did you find most impressive about this company?

I had no idea the power of data science technology! What Fast Data Science was able to do for my organization, in such a short amount of time, was unbelievable and opened our eyes to what is possible in the future for our other campaigns. We were also really happy to have found a company that was able to communicate with our team of non-data scientists in a way that was clear and totally understandable.

Are there any areas for improvement?

We were extremely pleased with every aspect of this project and with our working relationship with the Fast Data Science team.

BACKGROUND

Please describe your company and position.

I am the VP AI and NLP of Inspirata Inc.

Describe what your company does in a single sentence.

Medical software engineering focusing on cancer informatics

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire Fast Data Science to accomplish?

• Assistance with decomposing and parsing complex PDF's for patient data and clinical trial protocols.
• Use of LLM's to solve component of a problem in our AI Engine technology.

SOLUTION

How did you find Fast Data Science?

Referral

Why did you select Fast Data Science over others?

• High ratings
• Pricing fit our budget
• Great culture fit
• Good value for cost

How many teammates from Fast Data Science were assigned to this project?

1 Employee

Describe the scope of work in detail. Please include a summary of key deliverables.

NLP project for Parsing clinical text data.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

Software to parse complex PDF's for clinical data extraction.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

Thomas was basically included as part of our AI team - weekly meetings and other updates.  Communcation was very good through emails and online calls. Deliverables were on time.

What was your primary form of communication with Fast Data Science?

• Virtual Meeting
• Email or Messaging App

What did you find most impressive or unique about this company?

Thomas was very responsive and essentially became part of our team for the duration of the project. Fast Data Science's focus was on what we needed, and they were consistently willing to assist.

Are there any areas for improvement or something Fast Data Science could have done differently?

All good.

BACKGROUND

Please describe your company and position.

I am the Director, Product Management of Real Life Sciences

Describe what your company does in a single sentence.

Real Life Sciences helps Pharma Sponsors meet regulations EMA Policy 0070 and HC PRCI

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire Fast Data Science to accomplish?

• Identify sensitive information in clinical documents using AI

SOLUTION

How did you find Fast Data Science?

Online Search

Why did you select Fast Data Science over others?

• High ratings
• Pricing fit our budget
• Great culture fit
• Good value for cost

How many teammates from Fast Data Science were assigned to this project?

1 Employee

Describe the scope of work in detail. Please include a summary of key deliverables.

Fast data science helped develop multiple models to help better identify sensitive information in clinical documents

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

We saw a significant decrease in project processing times. 

Describe their project management. Did they deliver items on time? How did they respond to your needs?

Thomas from Fast Data Science was always on target amd goes well above and beyond

What was your primary form of communication with Fast Data Science?

• Virtual Meeting
• Email or Messaging App

What did you find most impressive or unique about this company?

They move quickly because they have the right skills and experience

Are there any areas for improvement or something Fast Data Science could have done differently?

Not at all, they are and have been a pleasure to work with