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LIMS: Laboratory Inventory Management System

The Idea

Today’s scientific laboratories face intense demand to keep innovating and improving lab productivity. The time that should be spent on scientific activities is diverted to non-core ones due to shorter deadlines and a high need for creative solutions.

The answer is LIMS, a comprehensive portfolio of solutions that offers the knowledge, software, services, and human resources required for today’s labs. These solutions include uptime optimization, lab analytics, and workflow solutions. Due to technological improvements, real-time reports are now available, making it simpler for laboratories to make decisions.


  1. A fully dynamic backend that allows for the instant creation of database tables.
  2. The client requested that the entire form- and report-creation process be dynamic, meaning that reports and forms should be user-driven and flexible. 
  3. Users, even those without the slightest coding expertise, are able to create any type of form or report.
  4. To completely protect user data privacy by utilizing a SAAS-based platform.
  5. Complex data structure: Laboratory inventory systems are required to handle a sizable amount of data, including a wide range of items, their locations, amounts, and expiration dates. Frequently, the system must also interact with other laboratory management systems. Thus, creating a reliable data structure that can manage this complexity proved difficult.
  6. Customization requirements: Each laboratory has specific inventory management demands based on the kinds of research or testing it conducts and the variety of tools and materials it must keep track of. Thus, it was challenging to create a system that can be altered to satisfy the particular needs of each laboratory.
  7. User interface: A laboratory inventory management system’s user interface must be simple to use and intuitive because laboratory personnel will be engaging with it frequently. It was very difficult to make the interface such that personnel could quickly and simply access and manage inventories.


  1. Used a dynamic schema. We made advantage of a dynamic schema, which enables instant table creation. The schema can be created so that tables, columns, and indexes can be created dynamically based on user input. In order to make sure that only legitimate data is kept in the tables, the schema can also be checked. 
  2. Used a NoSQL database. NoSQL databases were used to store unstructured data, making it simpler to generate tables on-the-fly. As opposed to conventional relational databases, NoSQL databases are more adaptable since they frequently use a key-value store or document store to store data.
  3. Used a database migration tool. To handle dynamic database schema changes, we employed a database migration tool like Flyway or Liquibase. When new data is added, these tools are set up to automatically construct tables and update the schema.
  4. Used a microservice architecture. Specialized services have been developed using a microservice architecture to handle certain activities, such as building database tables. Each microservice has its own database instance that is used to dynamically construct tables.
  5. Used an ORM (Object-Relational Mapping) tool. We have used an ORM tool, like Mongoose, to map database tables to objects in the code. Based on the object definitions in the code, the ORM tool is used to instantly create tables.
  6. We had to use form.io and report bro a type of form and report designer as an outside resource, to fix the form and report issue. A drag-and-drop interface is made using a form and report builder to enable users to dynamically create forms and reports. Users may simply add, remove, and alter form fields and report components thanks to the designer’s user-friendly interface.
  7. Ensuring complete privacy of user data when using a SAAS-based platform was challenging, but we followed a few possible solutions to overcome from the same.
  8. Complex data structure: A possible solution we have employed is to use a well-designed database structure that can handle complex inventory data. The database is normalized to reduce data redundancy and improve data integrity. Additionally, using a robust data management system, such as a NoSQL database or an object-relational mapper, simplified the management of complex inventory data.
  9. Customization requirements: To meet the unique requirements of each laboratory, the inventory management system has been designed with a modular architecture that allows for customization. The system is built with a set of configurable features and parameters that can be adapted to meet the specific needs of the laboratory. Additionally, the system is designed with a user-friendly customization interface that enables users to configure the system to meet their specific requirements.
  10. User interface: A well-designed user interface that is intuitive and easy to use has been developed by conducting user research, which involves understanding the needs and expectations of laboratory staff. The user interface has been designed with a minimalist approach, using clear and concise language, icons, and visual cues to improve usability.

Project Glimpse

Technology Stack


React Redux




  1. Identification of the requirements. The first step in developing a laboratory inventory management system was to identify the system’s requirements. This includes defining the data to be collected, identifying the users and their roles, and determining the features and functionalities required.
  2. Selection of a development platform. There are several development platforms available for building laboratory inventory management systems. These include web-based platforms such as Django and Ruby on Rails and desktop-based platforms such as Java and .NET.
  3. Designing the database. The database is the heart of the laboratory inventory management system. The database is designed to store all the necessary information in a structured and organized manner.
  4. Development of the user interface. The user interface was designed user-friendly and intuitive. The interface allows users to easily navigate through the system and perform the necessary functions.
  5. Implementation of security measures. It’s important to implement security measures to protect the data and ensure that only authorized users have access to the system. This includes password protection, data encryption, and data access controls.
  6. Testing the system. Before deploying the laboratory inventory management system, it’s important to thoroughly test the system to ensure that it is functioning as expected. This includes conducting unit testing, integration testing, and user acceptance testing.
  7. Deployment of the system. Once the laboratory inventory management system has been tested and is functioning properly, it has been deployed. This includes installing the system on local servers or deploying it to a cloud-based platform.

A thorough approach to software development is necessary to create a laboratory inventory management system. The specific needs of the lab, the volume and complexity of the data, and the amount of functionality required will all influence the choice of solution. It’s crucial to collaborate closely with the laboratory workers to make sure the system is functional and easy to use.

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