Today, empowered patients and increased attention to drug safety have made pharmacovigilance more essential than before. Besides, the traditional pharmacovigilance process is highly manual and resource-intensive. As a consequence, pharmaceutical industries require deploying more robust processes and systems to detect, assess, report, and prevent adverse effects.
When it comes to accumulating information on adverse events (AEs), it starts right from clinical trials and continues even after the drug's market release. AEs are reported across the globe in different languages and formats. Some are structured or unstructured, whereas others can be reported as hand-written documents. Moreover, this data comes from multiple data sources – distributors, affiliates, partners, and even patients.
Estimates put that a huge pharma company receives 300,000 to 500,000 adverse events in a year. Large teams analyze these documents manually, identify the relevant information, and then enter them into the safety system. This data is followed by quality and medical review and later submitted to regulatory bodies.
With increasing patient awareness, regulatory pressure, and emerging data sources, there will be an exponential growth in data volume. Thus, pharmaceutical companies require shifting their focus from manual data entry to proactive management. With document automation technologies, pharma companies can decrease their efforts, time, and resources spent on manual data assessment; thus, freeing resources to concentrate on more crucial PV activities.
When it comes to creating a stack of documents every day, there is no doubt that it is painstaking and takes up a lot of time. But what if there is a way that could make this process easier and faster? Well, this is what document automation comes up along with a host of other benefits. Yet, many pharma companies deny from taking up such benefits, thinking that document automation cannot generate complex documents, it might require specialized training to learn how to use it, or it is too expensive for their organization.
But, with varied data sources and immensely growing PV data, it is high time pharmaceutical companies bust these myths and adapt to the most efficient document automation systems.
Once deployed, the document automation system will reduce manual efforts by 70-80%, while ensuring zero data entry errors. Besides, it eliminates time-squandering processes like data extraction, data entry, document generation, and report creation, ensures accuracy, and saves money.
There are a lot of processes involved in pharmacovigilance from the collection of Adverse Events, processing, signal generation, and more. It takes up a lot of human resources, money, and skilled management. As pharmacovigilance must have minimum errors, quality workforce and management are crucial. Document automation in pharmacovigilance circumvents the need for human resources. As most of the tasks performed are repetitive, they can be automated.
Employing document automation in data processing will not only reduce costs but also accelerate the processing. Moreover, it will eliminate the risk of human error while improving quality and accuracy. This can help PV industries establish a robust pharmacovigilance system that utilizes modern technology to capture and analyze new data sources. The document automation system thus enables pharma industries to automate the extraction of data and the process of reporting.
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Adds various capabilities such as inequalities,descending sort, joins, and other functions.
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SQL Select Debugger
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Added a Query tab as a field for typing or pasting in a select statement
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All tags using that Data source will be automatically updated with that name.
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New single interface to replace 2 separate dialog boxes
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Displays of all the tags in the template, structured as they are placed in the template. This provides a simple & intuitive way to see the structure of your template. Also provides the capability to go to any tag and/or see the properties of any tag.
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The ability to integrate the Windward Engine into Google’s cloud computing platform for developing and hosting web applications dubbed Google Applications Engine (GAE).
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This new integration will allow for processing of complex scripts and bi-directional text such as Arabic. Your PDF output will be much tighter and more closely match your template, and we’ll be able to respond rapidly to PDF requests and fixes.
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Includes support for new ForEach and slide break handling, table header row repeat across slide breaks, and native Microsoft support for charts and images.
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Tags are color coded in the template by type, making it easy to visually identify them.
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Version 13’s core code has been reworked and optimized to offer a reduced memory footprint, faster PDF generation and full documentation of supported features and limitations in the specifications for DOCX, XLSX and PPTX.
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Documents can include advanced Word image properties such as shadows, borders, and styles.
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Windward has updated HTML output to reflect changing HTML standards.
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Windward now works with a slew of new datasources: MongoDB, JSON, Cassandra, OData, Salesforce.com
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The Generate Code tool in the designer allows you to open an existing template and, with a click of a button, automatically create a window with the code needed to run your current template with all data sources and variables. Simply copy this code and paste into your application's code in the appropriate place. You now have Windward integrated into your application.
You only need to do this once. You do not do this for each template. Instead, where it has explicit files for the template and output, change that to parameters you pass to this code. Same for the parameters passed to Windward. This example uses explicit values to show you what to substitute in where.
Any pivot tables in an XLSX template are carried over to the XLSX output. The ranges in the pivot ranges are adjusted to match the generated output. So your final XLSX will have pivot tables set as expected in the generated file.
This makes creating an XLSX workbook with pivot tables trivial.
In an imported sub-template, if its properties for a style (ex. Normal) differ from the parent template's properties for the style, the use in the sub-template can be set to either use the properties in the sub-template, or the properties in the parent.
You set to retain when you don't want the child template's styling to change when imported. You set to use the parent when you want the styling of the imported template to match the styling in the parent.
Any explicit styling is always retained. This only impacts styling set by styles.
Tags can be placed in text boxes. Including linked text boxes. This gives you the ability to set the text in a textbox from your data.
Tags can be placed in shapes & smart art. This gives you the ability to set the text in a shape from your data.
When generating HTML output, the engine can either write bitmaps as distinct files the generate HTML references, or it can embed the images in the HTML providing a single file for the output.
You can place tags in pretty much any part of a template, including in footnotes & endnotes.
Any parts of a DOCX or XLSX (PowerPoint does not support this) file that are locked in the template, will be locked the same in the output.
If a font used in the template does not exist on the server generating a report, the font to substitute can be specified.
In addition, if a glyph to be rendered does not exist in the font specified, you can specify the replacement font. This can be set distinctly for European, Bi-Directional, and Far East fonts.
If you need this - it's essential. And if you don't need it, it's irrelevant.
Windward enables you to build a document by applying multiple datasources to the template simultaneously. When Windward is merging the data into a template, it processes the template by handling each tag in order, and each tag pulls from different datasources. (As opposed to processing all of one datasource, then processing the next.)
This allows the select tag to use data from another datasource in its select. For example, if you are pulling customer information from one data source, you can then pull data from the sales datasource using the customer ID of the customer presently processing to pull the sales information for that customer. If you're interested in patching together your data from multiple datasources, read this post on our blog.
