Laboratory Information Systems (LIMS) for biotech startups
The Biotech sector is future-facing, exciting, and ablaze with promise.
The projected growth of the life sciences industry is almost impossible to gauge, with such diverse industries as paper, textiles, biofuels, food, healthcare and agriculture seeking biotech-driven innovations to better their outcomes.
Some of the biggest challenges biotech startups face are building out internal tools for data collection and prototyping new innovations. Information technology is by now a well-known accelerant in the field of biotech research, with big data and the tactical connectivity of knowledge bases combining to increase R & D efficiencies, and decrease time to market for these products. But the connectivity and networks so central to biotech momentum present thorny security challenges.
In biotech pharmaceutical research, the sanctity of personal health information (PHI) is a north star, and a constant source of concern. Docframe is a no-code database solution that allows a biotech company to easily build its own HIPAA-Compliant applications for their internal operations—all without having to write a single line of code. Pharmaceutical innovations require human subjects for pre-clinical and clinical trials. The safeguarding of individual medical records in the biotech setting is an ethical, legal, and practical responsibility. The day the public stops trusting the biotech sector to safeguard their private medical information is the day the public stops answering the call for volunteers—the lifeblood of biotech R&D and clinical trials.
Many Biotech companies have to make the difficult choice of building out a tool from scratch for their internal operations, or having to choose a SaaS product whose non-configurable fit is at best imperfect. Docframe’s elastic capabilities speak to biotech’s focus on cost management. An internal team whose primary role is caretaking and customizing the enterprise system is an expense that needn’t add to biotech’s already massive financial outlay. Docframe’s no-code design allows a company to continually improve and enhance their own spreadsheet-like database to a level of sophistication that fits their changing needs. Docframe’s simplicity of process drastically reduces the barrier to entry in prototyping new products, and reduces the time it takes to launch. Here are Docframe’s primary features.
“HIPAA-Compliant” is the highest standard of data security, ensuring that a company has met the government’s federally mandated standards for securing private medical records. Docframe has been designated HIPAA-Compliant, meeting and exceeding all legal and technical requirements around Protected Health Information (PHI) and Electronic Protected Health Information (ePHI). The 1996 Kennedy–Kassebaum Act, known more familiarly as HIPAA ( the Health Insurance Portability and Accountability Act), was created and signed into law in 1996. Why? That year the personal computer was becoming an increasingly common appliance in the home and in business. The information-sharing wonders of the digital age promised both great cultural advances, and a threat to privacy through vulnerable, electronically stored personal records. Docframe—developed to align with biotech’s critical need for security and simplicity—provides an out-of-the -box HIPAA Compliant, no-code platform that is easy to use, maintain, customize, and master.
Role-based access controls are a set of predefined permissions that attach to and define an employee’s access. That is, the employee’s degree of access to the database is joined inseparably to that employee’s role, the user allotted only that access defined as an essential component of their role. Permissions are inherent in the role and travel with the role. When a colleague’s responsibilities change, that user’s assigned new role, and nothing else, determines the user’s new degree and kind of access. Role-Based Access Controls are distinct from Discretionary Access Controls, which put the access-granting discretion in the hands of a person or group designated as gatekeepers. Role-Based Access Controls are by definition self-policing, and subject neither to discussion or the interpersonal dynamics of the workplace.
Transactional Data Validation is a way to build in protections against manual data entry errors that can skew output. It means that at the field-creation level, manual data input is loudly auto-rejected unless correctly matched to the field being populated. What specific category of entry will the field allow? Is the entry type a Number? Letter? Date? The array of data entry types allowed in a given database can be incredibly broad and varied, and the more complex and numerous the entry types, the greater the possibility of human error warping the dataset. A consistent, slip-proof data entry environment means you can trust your output. The data may not say what you’d hoped, but that won’t be because of errors in entry. Carefully tailoring and locking field entry parameters makes scaling less worrisome, too, as greater employee access won’t come bundled with an increase in the odds of bad entries. Docframe’s Transactional Data Validation ensures a clean and accurate dataset that scales, and yet offers the manual input simplicity a spreadsheet-like UI.
A Relational Database – as its name implies – is a structure for classifying data into different categories and datasets, and relating/connecting those data points to each other for efficient storage and retrieval. The relational database provides links between distinct datasets whose data points can then be sorted against each other to produce a new data set. Such linkages in an Excel spreadsheet, for instance, are code-heavy and limited. Docframe provides a native way to link information between different datasets — but on a familiar spreadsheet-based UI.