Saturday,  Nov. 18, was not a typical Saturday for some students at Montgomery County Community College. For a handful of select students, this was a day they chose to challenge themselves by applying to an invitation from Merck & Co. to participate in an automation challenge. As they descended upon the campus, there was an excitement in the air as they stepped into the unknown. Some thought they were going to execute a canned set of exercises, and others were unsure about what was about to transpire.

The cohort of students included Zachary Denmark (Biotechnology), Joseph Todd Fredericks (Biotechnology), My Ly (Engineering), Maria Naeem (Biotechnology), Janet Nguyen (Computer Science), Thomas Quinn (Engineering), David Siegfried (Computer Science) and Jessica Witmer (Biotechnology). Together, they would be putting their skills to the test over the next three days.

Merck’s Director of Scientific Automation, Scott Ziegler, who designed the challenge, and several Merck scientists were on hand to guide the students, as well as Dr. Maggie Bryans, MCCC Biology Associate Professor, and Dr. Chengyang Wang, MCCC Engineering Assistant Professor.

Day 1 – Saturday, Nov. 18

This was a training day, a day to level set everyone with the same skillset to help ensure their success and to impress upon them the need in automation for cross-disciplinary skills. The day began with introductions and nourishment. At 9 a.m. the students headed for the biotechnology lab where they all participated in pipetting skills, and they competed with one another in a competition for accuracy. They executed a lab, pipetting 10 different volumes and computed their pipetting accuracy. This was followed by the execution of an ELISA assay where they processed four patients and determined how many responded to a vaccine.

Around 12:30 p.m. the cohort headed back to the engineering labs for the next phase of their training, operating and programing a Staubli 6-axis robotic arm. The session was taught by a representative from Staubli and began with lecture followed by hands-on practice. The cohort learned about safety, movement in 3-D space, robot teaching, approaches, and the VAL3 programming language. They moved from the desk to the robot and were able to get their hands on the system and make the robot function as they learned how to teach it and review demonstration code. They wrapped up this three-hour session and were eager to continue with the robotic arm.

From the robot, they moved into learning how to write code using the Python programming language and the Jupyter integrated development environment. The session began with the very basics, and as each topic was introduced, they executed a programming exercise. After three hours of skills building, they were taught the basics of bar code scanners/codes and the  RS-232 communications protocol where they also executed a hands-on lab writing code to control a relay over RS-232.

This night culminated with the big reveal, the challenge. They were presented with a hypothesis that stated "Many of my colleagues have varying opinions related to automation in science. One prevailing opinion, or hypothesis, is that automation is a wasted effort. Your challenge is to prove or disprove the hypothesis." Then they were presented with the challenge itself and told that they would be automating the pipetting challenge lab they executed earlier that day. When they executed the lab they pipetted 10 volumes into a single vial. Now they have up to 100 vials to pipette. The tools they were given included the Staubli to move the vials, a balance to weigh the vials, a bar code scanner to read the vial identifiers and a Mantis robotic liquid handling device. They were to manually pipette up to 50 vials and automate liquid dispensing for the other 50. In the end they needed to compare their accuracy between the manual and the automated, the accuracy between each person, and the accuracy compared to themselves.

At this point it is about 8:30 p.m., and we have been at it for 12 hours. One would have thought they would have bolted for the door when they got the reveal, BUT, they did not.  They dug in and started brainstorming ideas. Around 9:30 p.m., they swapped contact information and setup a group chat. They headed out after 13 hours ready to hit the ground running. We discovered that they spent all day Sunday thinking, reading, chatting with each other preparing for Monday.

Day 2 – Monday, Nov. 20

When the staff arrived at 8 a.m., an hour before the start, some students were already waiting. Once the lab was opened, they immediately dug into brainstorming. Once they all arrived, we reviewed the challenge, presented all of the tool and components they had at their disposal (some of them were a ruse), and we asked them to hit the whiteboards and develop a plan of attack.

After an hour, they assembled and presented their approach to solving the problem. When the coaches heard their plan, we added some requirements, told them no to a few things, and sent them back to the whiteboard. After another hour, they presented again and this time they got the green light to proceed. They conducted a work breakdown, similar to what a project manager would do, broke into work groups and assigned tasks to the groups and got started. The coaches monitored their progress to ensure they were not heading in the wrong direction but did not tell them how to do things. They had to figure it all out on their own. We stopped a few times through the day to see where they were and redirect, if needed.

The cohort worked diligently all day, hardly ever stopping for a break. They made great progress, and the last student left at 9:45 p.m., after almost 13 hours.

Day 3 – Tuesday, Nov. 21

Again, there were students ready to go by 8 a.m. for a 9 a.m. scheduled start. They worked through the day solving the problems that arose while the coaches gently guided, suggested, and monitored their progress. They operated believing they had until 8 p.m. to complete the assignment. At 3 p.m., just like in the real world of ever-changing priorities, we announced they would provide a readout at 6 p.m. for a vice president within Merck so he could decide if he should invest in automation. This added a level of pressure, which helped to push them even harder.

At 6 p.m.,  we had a fireside chat with our vice president,  and they discussed their findings, what they learned, their impressions of automation and the need for cross-disciplinary skills in automation. After chatting for a while, we took a break, and some went back to working with the robot and others discussed the outcomes. We worked on cleaning up the space and ended the day around 9 p.m. with final farewells, another 12-hour day.

So, after 38 hours of structured time and who know how many hours on Sunday, they emerged with a new appreciation for biotechnology, engineering, and computer science. They have a solid understanding of the challenges with automations, felt the pressure of real-world timelines, experienced success and failure, and learned how to work as a team. One of the first questions at the end, was “when is the next one,” and then “how can we keep this going.”

It is worth noting that the students discovered that this was not a canned problem with pre-defined steps. They had to figure out solutions on their own, even when seeking guidance from the coaches. The coaches pushed the students to solve their own problems rather than providing direct solutions.

Overall, the  experience outlines a fascinating journey of students challenging themselves, acquiring new skills, and adapting to solve complex problems through cross-disciplinary collaboration.