A system for monitoring one or more lab processes and predicting their
outcomes, the system comprising:
a data acquisition module configured to acquire at least one of: ambient data and experimental data in real time from one or more lab resources and instruments;
a process setup and monitoring module configured to receive the acquired data and facilitate setting-up and monitoring of one or more processes in real time utilizing the received data; and
an experiment prediction module configured to:
obtain data from the data acquisition module and process setup and monitoring module; and
employ one or more machine learning techniques to generate one or more patterns to predict outcomes of the one or more processes conducted in the lab in real time.
2. The system of claim 1, wherein the one or more lab resources and instruments comprise Internet of Things (IoT) enabled lab instruments, computer connected lab instruments, lab and enterprise systems, time series database systems, existing Application Programming Interfaces (APIs), content libraries, voice inputs from one or more lab technicians and investigators working in the lab, and data historians.
3. The system of claim 2, wherein the voice inputs from one or more lab technicians and investigators are acquired using an artificial intelligence based virtual lab assistant.
4. The system of claim 3, wherein the virtual lab assistant is further configured to guide the one or more technicians to follow a predefined protocol adopted by the lab for capturing the voice data.

5. The system of claim 3, wherein the virtual lab assistant employs a cognitive
agent to perceive and act upon voice inputs.
6. The system of claim 1, wherein the process setup and monitoring module is
i configured to setup the one or more processes using one or more recipes created by a
recipe builder tool.
7. The system of claim 7, wherein the recipe builder tool is configured to create
software codes associated with the one or more recipes with every user interaction.
)
8. The system of claim 6, wherein the recipe builder tool has customizable prebuilt
templates of unit operations and parameters associated with the one or more recipes to
setup the one or more recipes, further wherein the customization comprises editing
properties of the prebuilt templates to make them compliant to one or more business
> requirements.
9. The system of claim 6, wherein the one or more created recipes facilitate
creation of one or more campaigns for one or more drug candidates, wherein campaign
of the one or more campaigns have one or more lots.
)
10. The system of claim 9, wherein the one or more lots are monitored for variation
in range values of the one or more parameters associated with the one or more
processes.
i 11. The system of claim 10, wherein alerts are triggered by the process setup and monitoring module when status of a parameter of the one or more parameters varies from a predefined range of values.
12. The system of claim 1 further comprises a resource tracking module configured i to obtain the data associated with the one or more lab resources and instruments and facilitate tracking, mapping and planning of the one or more lab resources and instruments using the obtained data, the resource tracking module is further configured to generate one or more reports on usage and efficiency of the one or more lab resources and instruments.

13. The system of claim 1 further comprises a content library communicatively coupled to the experiment prediction module and configured to provide access to one or more internal and external content providers and tools to facilitate prediction of outcomes of lab processes.
14. A method for monitoring one or more lab processes and predicting their outcomes, the method comprises:
acquiring at least one of: ambient data and experimental data in real time from one or more lab resources and instruments;
setting up one or more processes in real time utilizing the acquired data, wherein the one or more recipes are set-up using one or more recipes generated by a recipe builder tool;
monitoring the one or more processes in real time; and
predicting outcomes of the one or more processes based on their monitoring and the acquired data, wherein one or more machine learning techniques are employed to generate one or more patterns to predict outcomes of the one or more processes conducted in the lab in real time.
15. The method of claim 14, wherein the one or more lab resources and instruments comprise Internet of Things (IoT) enabled lab instruments, computer connected lab instruments, lab and enterprise systems, time series database systems, existing Application Programming Interfaces (APIs), content libraries, voice inputs from one or more lab technicians and investigators working in the lab, and data historians.
16. The method of claim 14, wherein the recipe builder tool is configured to create software codes associated with the one or more recipes with every user interaction.
17. The method of claim 16, wherein the recipe builder tool has customizable prebuilt templates of unit operations and parameters associated with the one or more recipes to setup the one or more recipes, further wherein the customization comprises

editing properties of the prebuilt templates to make them compliant to one or more business requirements.
18. The method of claim 14, wherein the one or more created recipes facilitate creation of one or more campaigns for one or more drug candidates, wherein campaign of the one or more campaigns have one or more lots, further wherein the one or more lots are monitored for variation in range values of the one or more parameters associated with the one or more processes.
19. The method of claim 18, wherein alerts are triggered when status of a parameter of the one or more parameters varies from a predefined range of values.
20. A computer program product comprising:
a non-transitory computer-readable medium having computer-readable program code stored thereon, the computer-readable program code comprising instructions that when executed by a processor, cause the processor to:
acquire at least one of: ambient data and experimental data in real time from one or more lab resources and instruments;
setup up one or more processes in real time utilizing the acquired data, wherein the one or more recipes are set-up using one or more recipes generated by a recipe builder tool;
monitor the one or more processes in real time; and
predict outcomes of the one or more processes based on their monitoring and the acquired data, wherein one or more machine learning techniques are employed to generate one or more patterns to predict outcomes of the one or more processes conducted in the lab in real time.