How to move from one dimensional data management to an efficient lab landscape

IDBS share how to address the problem of siloed data, the value of mapping out your laboratory landscape and what to bear in mind when automating



Pharma IQ
03/05/2019

scientist data capiture

Drug development productivity continues to fall, yet the pressure is rising on teams to find new insights at a faster pace. This is a difficult task when the data needed to drive discovery is siloed and one dimensional.

In this interview, April Pisek and Unjulie Bhanot, Solution Consultants from IDBS all share the challenges impacting drug development and discovery, how to map out the laboratory landscape and what to consider when transitioning to an automated system.

Deep Dive: Join April and Unjulie for their webinar at Smart Labs Digital. Secure your place here

 

Pharma IQ: What do you see as some of the biggest challenges people are facing during the drug development phase?

Unjulie: In both the bio-analytics and bio-process space, the focus is on time to market and making sure the drug is doing what it is meant to be doing, that it’s effective, potent and aimed at the right target. Companies will also be considering profit versus operational costs and reviewing how much regulatory scrutiny they are facing.

From a scientist’s perspective in the lab, they may be facing challenges from using manual or paper based processes. So they are seeing things in a very one dimensional format and they may be struggling with getting data out, preventing mistakes and tracking mistakes.

Some of their tasks may also be performed for the sake of compliance rather than supporting the science that is being done in the lab.

Challenges may include; one dimensional data, tasks which don't support the science, siloed data and outdated technology

The scientists may also be using outdated technology. If they (the instruments) are documented on a patent or filing document they may need to continue to support and maintain their kit, even if it is not performing in the same way as when it was purchased.

Another consideration is siloed data, they (scientists) may be facing the fact data lives physically in different space, in lab books, different excel sheets, different proprietary formats. This can cause a loss of insight into the data, along with delayed identification of issues and difficulties with collaborating.

April: One thing I’ve heard a lot of customers say is a big challenge for them is access to all of their data for collaboration.

Some may be using paper notebooks and Excel while storing information on their laptops and some on network drives. This can make it very difficult to find data, report on the multiple data sets and collate the data to achieve the higher level of meaning needed to know if a treatment is as efficient across multiple studies, for example.

A lot of customers struggle with access to their data for collaboration

The other thing that I’ve noticed is that when you have multiple sites in the company, it is very hard for them to be consistent with their naming conventions. That can lead to a mismatch of the data if people do not realize that they have used a different name.  

I’ve also seen a lot of customers wanting to integrate with multiple external systems. They may have a LIMS, other laboratory software, and instruments with additional software that are all processing their data. This means multiple places for storing data, so bringing everything together is definitely a challenge for them.

Find out more: Discover how to bring your data together in one system

 

Pharma IQ: What are some of the short term and long term impacts of these data inefficiencies across the drug development process?

Unjulie: In terms of short term impact, you will see reduced productivity, employees having to do re-work, late identification of issues and compliance failures. On a larger scale, you may then get compliance queries from regulators and customers and you can be in a very tough situation when it comes to audits.

In the short term, you will see reduced productivity, re-work, late identification of issues and compliance failures

Also, if you can’t deliver your work on time, that can have a direct impact on the company’s bottom line. This is particularly true for CROs as that may cause delays in payment. In the CMO and CDMO space you may also develop a  bad reputation in the market and poor credibility if (potential) customers find out you’ve had compliance queries or issues in the past.

Short term, it can have a big impact if you can’t get your data out to your customers.

If you’re a CRO, for example, then a pharmaceutical company needs their information to move a drug to the next stage. If a CRO cannot share the relevant data in a timely fashion, they are disappointing the pharmaceutical companies and stopping themselves from being able to move on to their next project.

April: Short term, every day that you can’t meet a deadline for a customer, you are delaying them from filing their drug to regulatory bodies, which is in turn lost revenue.  If you’re not able to report the data fast enough, that can have a long term impact on your reputation.  Even with a lot of companies out there,  people tend to move around, and that’s when rumours can really ruin a reputation.

Being slow to deliver can have impacts both on revenue and reputation

Unjulie: If people are hearing negative comments, they may also start to question the quality of the product that you are making. For CROs and CMOs, they may wonder if the testing or manufacturing is reliable. You can’t prove things if you aren’t documenting and consolidating that information and that can raise questions in the market.

 

Pharma IQ: What’s the solution for addressing this type of problem?

April: By using a single platform to encompass all the different business and laboratory areas.

If the data is stored in one system, it is much faster to retrieve than if it was stored over multiple systems. Being able to have everything the lab needs to operate, in one system, can help you create efficiencies, prevent mistakes, reduce re-work, report on data faster, and run more samples.

Unjulie: It’s important to think about the laboratory landscape as a whole and map out what it is you want to deliver. This way you can implement a solution that can deliver more than one functionality to different factions of the business.

Make sure to map out the laboratory landscape as a whole so you can really understand what it is you want to deliver

You have to think about the scientists entering their data at the point of running an experiment, where that data may have come from (for example reagent preparation performed by someone else in the lab), software used to process and analyse the data, and then the consolidation of this data and compilation of reports. These are all elements than play into the overall role of the business so finding a streamlined solution is quite important.

Organisations also need to look into moving away from paper. It is no longer a reliable and effective way to report data and pull it all together. This also links to out-dated technology, such as old systems which generate print outs, as these are not really conducive to the way people work now.

 

Pharma IQ: When a company is looking to move from a old fashioned, paper based enterprise to a singular information management system, what do they need to consider to prepare themselves for that transition?

Unjulie: Change management in key and bringing people on board.

Having the right sponsors and advocates in the business is really important. Senior stakeholders generally make the decision about buying this software but that message needs to be relayed down to the people who will be using it every day. They need to be given the change to experience and contribute hands on to the development of the software or at least the configuration.

April: Recently, I really liked the way a customer planned to implement one of our solutions with a phased approach. By introducing it to one group at a time, this can prevent a huge impact on the existing business. As the first laboratory gets used to the system and gets on board with the change, when they start gaining efficiencies it can enable the other business units to also get on-board, creating better user adoption.

Make the transition away from traditional systems in stages, engage the end users and work to create a system that is effective for all

At the previous laboratory where I worked, AIT Bioscience, when we first implemented IDBS E-WorkBook, the leadership team allowed the end users to shape the solution that fit the lab setting best. We were able to design the workflows to capture data in-line with how you would perform the work at the bench. By letting end users have an opinion, you definitely increase user adoption.

Unjulie: Following on from that, another thing to think about is other processes that run in a lab, for example reviewing experiments or sharing information to a customer. It’s important to think about how what you are doing now and the processes you use will change when you implement a solution that is electronic.

April: Absolutely – I have seen one lab who wanted to directly move their paper process to an electronic version. Instead, as you make this move, you need to start thinking about the data differently when you are doing it electronically.

When I demo our software, it’s important to remember that for many this is a huge paradigm shift, and I want them to understand that they’re not just using paper anymore.  You may still capture the same reagent names and equipment IDs, but when you want to search on the data entry, you will be learning more about your data than you ever could.

 

Did you enjoy this interview? Hear directly from April and Unjulie at the upcoming Smart Lab Digital Event. Sign up for your free pass now