SLAS International Debrief
Intro
I had a great experience this past week at the SLAS International conference in San Diego. I gained new enthusiasm for the space, and I made connections with other like-minded individuals looking to blend software, automation, and biology for cutting edge treatments. In this blog, I’ll highlight the impactful opening keynote, summarize some key findings, and share the new path I’d like to take in regards to my career.
Opening Keynote
The keynote began with updates from SLAS, new board members, and a statement from the CEO. This organization is committed to advancing science with cutting edge technology while looking to give back with initiatives in sustainability, mentorship, and a commitment to diversity. This commitment to diversity was further emphasized by the keynote speaker: Dr. Ahmar Zaidi who spoke about his experience working in black communities with sickle cell disease. He began with a detailed history of the discovery of sickle cell which led to a larger discussion about inequities black people face in the American healthcare system. Some key takeaways from this keynote:
History of Sickle Cell - We learned about the first cases of sickle cell and its ties to chronic pain as well as its prevalence in the black community
Racism in Healthcare - Doctors are less likely to believe black people who come to them for pain when compared to white people. Doctors who are aware that they have this bias are likely to course correct and provide better care to black folks, but this awareness is still not prevalent in healthcare. Because of this, there are jarring disparities in treatment, especially for black women.
Disparities in funding - Despite sickle cell having ~3x higher prevalence than cystic fibrosis, cystic fibrosis has far more funding and publications than sickle cell disease.
But why is this relevant to a conference about lab automation? I’ll give you two reasons:
We are here to help all patients get the treatment they need.
Rollback of DEI policies are happening in this country that will also affect the workforce.
I am Queer and Mexican American, and my duty as a scientist is keep these disparities in mind. As an employee, DEI is important so I can have the same career opportunities as my colleagues. As a patient, equitable clinical trials are important so all populations can receive equitable care.
A famous example of this disparity in healthcare is the relationship between skin tone and pulse oximetry. Pulse oximeters are not as effective when used on populations with darker skin. This crucial measurement relies on light passing through your skin to measure true blood hemoglobin oxygen saturation. This gap in care suggests an oversight in testing, particularly in communities of color. You can imagine the possibility of these disparities existing in other treatments.
This is further exacerbated with the advent of AI in patient care and diagnoses. If treatments are producing faulty data in communities of color, then how would training an AI on that faulty data be helpful?
Let it be known that I support DEI in all its forms, and carry those principles with me in my work. It’s comforting in this political climate that an organization like SLAS recognizes the importance of equity in the sciences.
Highlights
Some key focuses for me at SLAS this year were: automation and AI working together; fully autonomous workflows, and 3D cell culture. This list is by no means exhaustive, as much as I wish I could have attended every talk, it just wasn’t possible.
Automation and AI can go hand in hand, and there were plenty of examples at the conference. I’ll highlight a couple.
Opentrons AI turns your prompts into actual protocols in their GUI. The AI tool also turns your prompt into a Python script for GUI independent workflows. This is great for writing protocols from scratch and having the python script makes them easier to debug. Opentrons is known for the open source nature of their products, and this new AI tool supports that.
Evotec showed their in silico screening tools to support drug discovery efforts. With their in silico hit identification, chemical hits that may have been considered false negatives in an in vitro screen are reevaluated with their AI/ML screening platform. By increasing the diversity of compounds in your in silico screen, higher quality data is generated and validated in vitro. As we’ve discussed in this blog, in vitro assays, when paired with automation, produce higher quality data.
Fully autonomous workflows were on full display at SLAS. Whether we’re talking about all-in-one platforms from one vendor or tools meant to ease the integration of different instruments, a fully autonomous lab seems more obtainable than ever.
I’ve already talked about the Cellmatic from Formulatrix, but I was able to see a demo on the showroom floor. I got more details about this instrument, including its ability to perform hit picking protocols and sample tracking for clones. This is perfect for cell line development workflows.
The Celltrio Robocell was another great instrument that went beyond the plate format and split cells in T-Flask format. Most automation is done in plate format making scale up difficult. This instrument has the potential to scale up your cell culture workflows quickly because its fully autonomous nature means your cells are being split 24/7.
Unite Labs is an integration platform that gives developers and automation engineers the tools to make integration of hardware and software easier. As someone who does not have a developer background but wants to learn how to build their own integrations, this product has the potential to facilitate integrations with less support and faster than ever. Keep this in mind when you need to integrate different software and hardware packages from different vendors.
The Tecan Veya is a new robotic platform that comes at a much lower price tag than the Tecan Fluent Platform. It’s marketed as a user-friendly liquid handler with detection tools and digital connectivity that fosters walk-away automation.
3D cell culture
I learned about label free readouts of patient derived organoids using an ML algorithm to differentiate between dead and alive organoids in a seminar by Dr Seungil Kim from the Ellison Medical Institute. Remember, organoids can be a more clinically relevant model for in vitro assays, and making a label-free assay allows for reuse of live organoids for other studies.
The Orgadroid uses AI to sort organoids by size and move them into plates for further studies. This is important because there is variation when generating organoids. This got me thinking about applying automation principles to the generation of organoids because this much variation suggests an interoperability issue. Nevertheless, it’s a useful tool that’s applicable to various organoid types.
High powered imagers like the Cytation 10 and Operetta have the capability to image organoids and generate large amounts of data with high content imaging, a technology that I will cover in a subsequent post.
My passion for automation was reignited after attending this conference. Let’s talk about where I’m headed next.
What’s Next for Me?
Let me reintroduce myself, I’m Esteban Carabajal, a biotech professional with 10 years in the industry focused on automation engineering, cell culture, and high throughput screening. My overall career goal is to convince as many people as possible to use automation for their experiments. I bring technical expertise and a love of teaching to my work that will get your lab and scientists up to speed with new technologies.
Lab Automation as a discipline combines the automation hardware, software, and biology to generate high quality data that will be crucial for the trajectory of the industry. My personal development will emphasize the tools necessary to act as the interpreter allowing for hardware, software, and biology to work together. My focus right now is strengthen my coding skills to script robots and help build workcell integrations. I don’t plan to become a full on developer, but I’m hoping that educating myself in the space will help collaborations between scientists and engineers run more efficiently.
I’m also looking to foster the connections I made at SLAS and collaborate with other automation engineers and vendors for content and projects that will help drive science forward. Attending this conference as a freelancer was scarier in my head than it actually was. Talking with other folks about robotics, assays, integrations, and cell culture helped combat my own imposter syndrome. I know I have a place in lab automation, and I’m more determined than ever to carve out a space for myself.
I’m a firm believer that hard work will pay off and will keep chugging along. If you think we should work together, don’t hesitate to reach out!
Conclusion
Attending SLAS gave me hope that the industry is going in the right direction even if some things in the world seem to be going the opposite. Their dedication to addressing inequities in healthcare and showcasing of the newest technologies gave me hope for the trajectory of my own career. I’m hitting 6 months as a freelancer and 4 months making content, and I have to say that I’ve never been more passionate about what I do.