Death of a Child and the Prevention Thereof


Death is the water we swim in. 

Inevitable, and invisible, and everywhere. Like most, this isn’t something I used to think about too much.

But her death changed me. 


I started programming when I was 12, and freelancing successfully at 14. 

By 22, I felt like I had exhausted my interest in tech. I liked building things that people paid me lots of money for, but I didn’t care for expensive activities. Owing to this luck, I was living a semi-retired lifestyle. I spent most of my off-time reading and learning — which itself perpetuated the virtuous cycle that is semi-retirement for a programmer. But of course, eventually this arrangement grew boring.

I had always loved medicine, and I had always hated going to school. But I thought I’d love medicine more than I hated going to school. So I signed up for classes, and began the trek towards medical school. One of med school’s endless requirements is Shadowing — an ornate game of “Follow the Leader”, played inside a hospital. The physician was the leader; I, the follower; and the patients, a filter to make sure you really, really do want to attend medical school. 

And so it was that I shadowed a pediatric neurologist, touring the world of complications that arise when something is wrong with the brain. Most children we saw in the clinic were doing well. Smiling and laughing as the neurologist dissected their ailments with poking, prodding, and little games. I was enthralled! Filter passed, right?

But the gradient of children grew sicker as we approached the pediatric ICU. IVs replaced the smiling; beeping monitors replaced the laughter. Many patients were unconscious, and the parents filled this void with their own fretful intensity. 


Many of these parents had just started thinking about death. I remember when I started thinking about it too. 

The neurologist’s pager piped up asking, if he wouldn’t mind, for a consult. He dialed in, asked a few hushed questions, and we sped off through the maze of hallways.

We entered a secluded room in the ICU — a couple standing in the corner, younger than I at the time, but aging rapidly. In the bed, a mass of wires, a mass of tubes, and a mass of sweat-soaked blankets. 

And in that mass, a child. A ventilator hissed softly, and the child’s chest shuddered.

It was then that the neurologist I shadowed introduced himself to her parents — and started a conversation he had great practice with.

“I’m sorry, there’s nothing left for us to do. Your child is dead” 

Delicate pause. The words hung.

“The injury was too great” 

He gestured reservedly to a screen, an MRI and EEG purporting the same story.

“I don’t understand — is there not… more medicine?” 

Mom was disoriented.

Time acts strange in a situation like that. The mother asked variations of “Are you sure?”, to which my neurologist answered “Yes” — not cold… just inevitable.

At some point, they transitioned abruptly from “parents” to “couple” — and their world disintegrated. Despair roiled through the room. Mom and Dad clung to each other, as they collapsed into Husband and Wife.

My neurologist nodded his head, said he would be back to check in on them, and as we returned to the bustling maze of hallways… I started thinking about death then.


That was the end of the line for my dream of medical school. Filter failed. The complexity of disease is immense, and our current tools and processes are inadequate. Doctors and scientists can only stare at shadows on the cave wall. I can’t spend the next decade with a face in a textbook, only to be at the same place but wearing the white lab coat.

Medicine and biology have come far, but we have so far to go. I’ve spent a decade building skill sets across robotics, machine learning, and leading teams. On the right vector, with enough force of will, we can eliminate: “I’m so sorry, there’s nothing left for us to do”.

We’re building Transistor Bio — a new type of biocomputer that bridges nature and silicon, calculating better solutions to death. Fully automated, massively parallelized, we’re running in vivo studies with speed, rigor, and scale. A Pareto-efficient search of drug candidates and truly meaningful validation, all-too-absent in status-quo pharmacology, will slash both cost and time-to-market… time-to-patient.

But that’s just step 1.

– Adam 

CEO, Transistor Bio