Big Data / FDAAWARE Rafi Maslaton President, cresults the maker of Smart-QC/QA/QD & FDAAWARE 30-SEP-2015 1
Agenda BIG DATA What is Big Data? Characteristics of Big Data Where it is being used? FDAAWARE Introduction The usage of structure and non-structure information in our industry to mitigate compliance risk Examples Summary 2
What is Big Data: A definition Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. The challenges include capture, curation, storage, search, sharing, analysis, and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions. (Wikipedia) Put another way, Big Data is the realization of greater business intelligence by storing, processing, and analyzing data that was previously ignored due to the limitations of traditional data management technologies (Harness the Power of Big Data: The IBM Big Data Platform) The first organizations to embrace it were online and startup firms, like Google, ebay, LinkedIn, and Facebook were built around big data from the beginning. 3
What are the key drivers 2.5 quintillion bytes of data are generated every day! A quintillion is 10 18 Data come from many quarters: Social media sites Sensors Digital photos Business transactions Location-based data Source: IBM http://www-01.ibm.com/software/data/bigdata/ Facebook handles 40 billion photos from it s user base. Wal-Mart handles more than 1 million customer transactions every hour. Decoding the human genome originally took 10 years to process; now it can be achieved in one week. 4
Why Big Data Growth of Big Data is needed Increase of storage capacities Increase of processing power Availability of data (different data types) Every day we create 2.5 quintillion bytes of data; 90% of the data in the world today has been created in the last two years alone Big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings 5
Three Characteristics of Big Data V3s A typical PC might have had 10 gigabytes of storage in 2000. Today, Facebook ingests 500 terabytes of new data every day. Boeing 737 will generate 240 terabytes of flight data during a single flight across the US. The smart phones, the data they create and consume; sensors embedded into everyday objects will soon result in billions of new, constantly-updated data feeds containing environmental, location, and other information, including video. FDAAWARE needs Big Data isn't just numbers, dates, and strings. Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media. Traditional database systems were designed to address smaller volumes of structured data, fewer updates or a predictable, consistent data structure. Big Data analysis includes different types of data Clickstreams and ad impressions capture user behavior at millions of events per second high-frequency stock trading algorithms reflect market changes within microseconds machine to machine processes exchange data between billions of devices infrastructure and sensors generate massive log data in real-time on-line gaming systems support millions of concurrent users, each producing multiple inputs per second. 6
Common Big Data Customer Scenarios IT infrastructure optimization Legal discovery Social network analysis Traffic flow optimization Web app optimization Churn analysis Natural resource exploration Weather forecasting Healthcare outcomes Fraud detection Life sciences research Advertising analysis Equipment monitoring Smart meter monitoring Source: Microsoft 7
Application of Big Data in Risk Assessments 8
Application of Big Data in Risk Assessments The examples are based on a platform using structure and non-structure information to project compliance risk for companies governed by the FDA. Fully integrated risk management platform with FDA CFRs for Drugs, Biologics and Devices By leveraging current and historical 483s/inspections details, recalls, warning letters etc., and in conjunction with an advanced Projection Algorithm, assesses specific sites and overall company compliance related risks (Source FOIA & Internet). The usage of non-structured data provides a significant added value, essential focus areas and critical information to assess the risk for companies, vendor(s) and supplier(s). We will show how Big Data analytics can be used as a practical application to analyze volumes of data to identify and pin point areas of risks 9
Examples of Big Data Analytics 1. Design a new aseptic facility: how to avoid making past mistakes related to compliance using an advanced search engine, which highlights historical observations related to this area 2. Validation: how to provide our team with higher risks areas that should be addressed and prioritized first 3. My Company Compliance Risk: how to leverage some analytics to minimize our compliance risk 4. 3 rd Party Audit: how to leverage various information sources towards focused audit on site 5. Company Compliance Benchmark: how do you compare to your competition 6. Few Examples 10
Structure/Non-Structure Date Data Sources 483s & Responses 17,000+ Inspections 40,000+ (2008-2015) Recalls (Weekly) Since 2012 (16,000+) Recall Press Release (On Going) Warning Letter (On Going) Inspectors History 2,000+ Inspectors Adverse Events 11
PDF/IMAGE/TXT Processing the 483 Questionnaire, site profile Algorithm Reports/KPI Remediation Plan Data Flow - Overview Reduce Compliance Exposure and Business Risk Reports / KPI Processing the 483 Severity Keywords Context Warning Letters Areas Allocation Quality Systems. Algorithm PDF / IMAGE TXT - Confirmation Upload Fully Linked to 21 CFR Manage Remediation Projects Questionnaire, site profile Project Progress Report Remediation Plan 12
Designing an Aseptic facility Ability to search ALL historical 483s where Aseptic processing was cited, including information such as companies, industries and content Source: FDAAWARE 13
Designing an Aseptic facility Ability to search ALL historical 483s where Cleaning was cited, including information such as companies, industries and content Learn from structured/non-structured DB about areas in which other companies were cited to avoid costly mistakes Source: FDAAWARE 14
Designing an Aseptic facility What are the information sources are used? 483s PDF file (Non-Structured) Code of Federal Regulations (Non-Structured) Title 21Food and Drugs Converting a non-structure information that is available via FOIA to a value added input into the design stage 15
Validation Key Word Ability to search ALL historical 483s where Validation was cited, including information such as companies, industries and content Source: FDAAWARE 16
Validation Key Word How to leverage non-structured information that is available via FOIA to prevent us from making the same mistakes others made Advanced search engine provides compliance, validation and engineering teams the ability to focus on details that are easily overlooked Source: FDAAWARE 17
My Company Top Risks - Executive Dashboard High Risk areas are highlighted on the TOP Source: FDAAWARE 18
3rd Party Audit Using structure and non-structure information to assess our vendors risks Source: FDAAWARE 19
Company Compliance Benchmark Using structured and non-structured information to compare various selected companies in various compliance related areas Source: FDAAWARE 20
Few Trends - Example Source: FDAAWARE 21
FDA Auditor Statistic Source: FDAAWARE 22
Summary In Today s complex and costly compliance space, companies must leverage all information sources (Structured and Non-Structured) to better align with the latest compliance requirements Leveraging some of the new Big Data tools can facilitate this process and enhance a company s ability to manage their compliance related risks FDAAWARE leverages various information sources to better equip companies with analytics needed to manage risk, prepares companies for inspection and focuses their compliance team on areas that have been identified by the FDA as critical When facing limited cost, resources and time, the usage of technology, an advanced algorithm and analytics, is crucial in order to minimize risk 23
THANK YOU 24