Listen to the next episode of our podcast, Under the Surface. In episode 18, The FoF (Filet-O-Fish) Turning Point to OpenFF (Open Force Field), we chat with @Lily Wang, Science Lead at the Open Force Field Initiative (@OpenFF), about the unexpected, very human moment that set her on the path to computational chemistry — a cold Filet‑O‑Fish eaten at 1 a.m. after a disastrous night in the lab.

Lily shares that she first wanted to study art. Still, a close friend's lupus diagnosis inspired her to choose science instead, leading to advancements in molecular simulation and force fields that benefit computational chemistry research.

We also cover recent advances in molecular modeling, such as neural-network-based charge models and improved protein force fields, to excite researchers about future innovations.

Topics:

• Lily's path from the arts to computational chemistry

• What OpenFF and OMSF actually do

• Building more advanced force fields

• Sage 2.3 and neural‑network charge models

• Expanding force fields for proteins and nucleic acids

• Funding open science and partnering with industry

Listener discretion is advised.

Timestamps:

• (02:27) What is OpenFF?

• (04:10) How to make models more accurate.

• (05:42) What made her want to be a scientist in the first place.

• (07:37) The moment she realized working with computers in chemistry was perfect for her.

• (15:42) How scientists use computers to study the outside of cells.

• (20:22) The difference between super-detailed and simpler computer models scientists use to study chemistry.

• (26:23) How sharing science models helps people in schools and company teams to make faster progress.

• (35:03) How scientists can share what they learn without giving away anyone's secrets.

• (46:18) What's new in Sage 2.3?

• (52:05) Why it's tricky to model electricity in molecules, and where scientists are going next with this research.

• (54:45) Two ways scientists build their models.

• (58:45) Looking ahead: Quantum mechanics and AI could change how scientists work in the future.

• (01:08:15) The Deschenes Dilemma: Lily shares what she might do if she weren't a scientist.
  
  

Resources & Links:

• Open Force Field Initiative 2.3

• Developing and Benchmarking Sage 2.3.0 with the AshGC Neural Network Charge Model

• OpenFF GitHub Repository

• OpenMSF (Open Molecular Software Foundation)

Connect with Lily Wang:

• LinkedIn

*Content Warning: This episode includes discussions of trauma, loss, and near‑death experiences. Please take care while listening, and reach out to a mental health professional or someone you trust if these topics become overwhelming.*

Listen to the next episode of our podcast, Under the Surface. In episode 17, Building Collaborative Drug Discovery Tools, we feature an in-depth interview with Barry Bunin, CEO of Collaborative Drug Discovery, about his journey from chemist to entrepreneur. He shares how his background and desire to make a difference have shaped his company's mission and technology.

Here's what we discuss:

• Barry Bunin's background and what inspired his purpose

• How CDD started and became a leader in sharing science safely

• Why CDD Vault was built to keep research private, secure, and easy to use

• How teamwork and sharing data make drug discovery faster

• Finding the right balance between sharing and privacy

• How new tech like AI helps scientists work together

• Caring about people, having an impact, and doing good in science

• Barry's book shows the power of working together and being creative

This episode brings together science, entrepreneurship, and the personal stories that inspire innovation.

Listener discretion is advised.

TIMESTAMPS:

• (03:00) Barry talks about starting out in science, wanting to make a difference, and how that shaped his work.
• (06:00) How Barry's personal experiences led to his book and his current journey.
• (06:33) Content Warning begins.
• (07:10) Content Warning ends.
• (10:00) Mixing hands-on chemistry with computer tools to get better results.
• (15:00) How Barry got interested in combining chemistry and technology early on.
• (20:00) Moving from lab work to starting software companies.
• (25:00) What CDD stands for: their values, company culture, and mission.
• (30:00) Working together in drug discovery, and how to keep things open but private.
• (33:24) Content Warning begins.
• (37:33) Content Warning ends.
• (35:00) Real stories from the field, and why being human matters in science.
• (40:00) Keeping data safe and models using tech like federated learning.
• (50:00) How Barry's book came together.
• (1:00:00) Looking ahead: AI, collaboration tools, and making a positive impact.
• (1:06:40) The "Deschenes Dilemma": What happens if you can't stop doing science?
• (1:08:00) Thinking about legacy, inspiring future generations, and making your mark.
  

Resources & Links:

• Inside CDD Vault — A Different Kind of Silicon Valley Success Story: Behind the Code: The Human Side of Collaborative Drug Discovery (on Amazon)

• Collaborative Drug Discovery (CDD)

• The Human Side of Collaborative Drug Discovery

• How Do B2B Companies Hold Onto Their Purpose as They Grow?

Connect with Barry Bunin:

• LinkedIn

Check out the next episode of our podcast, Under the Surface. In episode 16, When Proteins Move: Woody Sherman on Computational Chemistry, Molecular Simulation, and the Future of AI in Drug Discovery, we chat with Woody Sherman, Founder and Chief Innovation Officer at PsiThera, and a longtime leader in computational chemistry, about how he went from studying quantum polymers to shaping modern tools like Induced Fit Docking.

Woody shares the moment that pulled him into protein simulations, his early exposure to AI at MIT, and how an internship at Biogen set him on the path to industry. He also reflects on his years at Schrödinger, building solutions, writing code, and learning how to solve real problems for scientists.

Topics:

• How application scientists help connect research with real-world industry needs

• Woody's journey from university research to starting Silicon Therapeutics

• How tools like induced fit docking were created

• How drug discovery platforms have changed over time

• What's different between working in industry and in academia

• What's next for open molecular software and AI working together

(02:05) Why mentorship matters for scientists

(04:15) Woody's path through school and research

(09:10) Shifting into custom molecular simulations

(12:00) Going from the academic world to industry

(15:00) Creating new tools for drug discovery at Schrodinger

(22:10) Putting together a team of experts

(26:15) Working together on drug design platforms

(34:00) Leading application science teams around the world

(41:45) Starting up Silicon Therapeutics

(45:58) Progress in the development of the STING agonist medicine

(49:00) Launching PsiThera

(56:30) Focusing on inflammation and the immune system

(60:15) Sharing science and data openly

(69:00) How AI will shape the future of drug discovery

(80:30) What Woody enjoys outside of work

(82:20) Final thoughts and getting involved with the community

Listener discretion is advised.