Brief Overview

This episode of Post Reports explores Silicon Valley’s rapidly expanding efforts to “optimize” babies through advanced genetic testing of embryos. Host Elahe Izadi and Silicon Valley correspondent Lizza Dwoskin dive into the world of startups like Orchid Health, which promise not just to screen for genetic diseases but to make predictions about a child's future health, sparking excitement, skepticism, and deep ethical debate. The conversation weaves through stories from families who’ve used these technologies, the evolving science, accuracy concerns, and the looming specter of eugenics.

Key Discussion Points & Insights

1. Introduction to Embryo Genetic Optimization (00:02–02:29)

• Orchid Health and Their Mission: Startups like Orchid offer advanced embryo genetic testing, positioning their technology as a step toward a future where all babies are "optimized" for health.
• Use of promotional videos to illustrate how families use these services.
• Genetic counselors guide parents through selecting embryos for IVF based on comprehensive reports.

“We went online and looked at all the results and then selected an embryo for implantation.”
— Parent in Orchid video promo (00:36)

2. What Makes Orchid Different? (03:38–05:34)

• Personal Motivation: Noor Siddiqui, Orchid’s founder, was motivated by her mother’s experience with a hereditary eye disease.
• Beyond Standard Testing: Orchid claims to sequence the whole genome from just five embryo cells, testing for 1,000+ rare diseases and making "polygenic predictions"—assessments of a person’s future risk of diseases like Alzheimer’s, obesity, or diabetes.
• Comparison to Routine IVF Screening: While genetic screening to avoid immediate fatal diseases is common, Orchid markets a much broader, more predictive scope.

“They're offering...over 1,000 possible rare diseases that a baby could be born with that they'll screen for.”
— Lizza Dwoskin (04:29)

3. Understanding Polygenic Prediction (05:34–06:52)

• The Science: Polygenic scoring aggregates genetic information from population biobanks (e.g., UK Biobank) to estimate disease risks based on gene clusters, but only in terms of probability, not certainty.
• Limitations: These scores show likelihood but do not make deterministic predictions.

“No one's saying you are going to get cancer if you have this particular constellation of genes.”
— Lizza Dwoskin (06:52)

4. User Experience and Access (07:03–10:43)

• Cost & Process: $2,500 per embryo; typically all embryos are screened for comparative selection.
• Reports & Decisions: Prospective parents receive detailed printouts for each embryo, comparing disease propensities.
• User Story – Roshan & Julie: San Francisco tech workers used Orchid to avoid passing on a rare hearing loss gene—polygenic scores served as a "tiebreaker" between otherwise similar embryos.

“We have six embryos. But two...very likely...will be born deaf, two are carriers...and two are completely unaffected.”
— Roshan George (10:13)

5. Accuracy and Scientific Concerns (13:25–15:56)

• Inconsistency Among Companies: Different startups give different risk predictions for the same embryos, suggesting unready technology.
• Algorithm Opacity: Each company has its own algorithms, none transparent or peer-reviewed.
• Sample Limitations: Most biobank data comes from people of European descent, reducing reliability for others.
• Questionable Methods: Scientists question the reliability of sequencing a full genome from five cells; Orchid’s only supporting paper is unpublished in detail and non-replicable.

“No one has been able to replicate the method or see how they actually do it. And a number of scientists told me that was cause for concern.”
— Lizza Dwoskin (15:56)

6. Ethical Dilemmas and Social Implications (16:09–20:40)

• Where Is the Line?: Most surveyed Americans are fine with disease screening but uncomfortable with trait selection (e.g., height, intelligence).
• Slippery Slope to Eugenics?: Host and guest discuss fears around reintroducing eugenics—a word with dark historical connotations—via technology.
• Equity Questions: Currently, only the wealthy can access these technologies, raising concerns about deepening social inequality—“designer babies by spreadsheet.”
• Genetic Complexity: Screening for some diseases may inadvertently “screen out” positive or neutral traits due to genes clustering together (pleiotropy).

“It also could just be that a lot of these wealthy people who are doing this are getting a little bit duped because polygenic scores for intelligence aren’t that good right now.”
— Lizza Dwoskin (17:49)

“If they had screened for [the mother’s eye disease], her mother wouldn’t have been born, and [Noor] wouldn’t have been born, and this company wouldn’t have existed.”
— Elahe Izadi (19:35)

7. Silicon Valley’s Motivations and the Road Ahead (20:40–23:13)

• The Ideology: Tech leaders see themselves as shaping the future. They argue for individual choice and the “democratization” of genetic knowledge, but acknowledge this frontier is deeply fraught.
• Normalization is Inevitable?: Lizza predicts broader adoption as the technology matures and prices drop, though not without controversy.
• Direct Eugenics Links: While Orchid refutes association with eugenics, they’ve platformed eugenicist academics (later removed after journalistic inquiry).
• Open Questions: Should biological advantage be added to the toolkit of the already privileged?

“Should we make [society] even more unequal with biology?...But the fact is this is already happening and people are already doing this.”
— Lizza Dwoskin (22:42)

Notable Quotes & Memorable Moments

• On Selection:
  “Families are literally...choosing the babies by spreadsheet.”
  — Unidentified Expert/Scientist (08:57)

• On Consumer Motivations:
  “Mostly they wanted to know that the baby didn’t have the hearing loss gene...the baby was born healthfully and does not have hearing loss.”
  — Lizza Dwoskin (10:36, 10:43)

• On Scientific Transparency:
  “Orchid says [their methods] are proprietary, but the effect is that no one has been able to replicate the method.”
  — Lizza Dwoskin (15:48)

• On Ethical Uncertainty:
  “A lot of these wealthy people who are doing this are getting a little bit duped...you might not be getting much at all for your money.”
  — Lizza Dwoskin (17:49)

• On Future Implications:
  “Society is already unequal with trust funds. Should we make it even more unequal with biology?”
  — Lizza Dwoskin (22:42)

Timestamps for Important Segments

• 00:02–02:29: Setting up the story: introduction to embryo genetic screening and Orchid Health
• 03:38–05:34: Noor Siddiqui’s personal motivation and Orchid’s unique approach
• 05:34–06:52: Explanation of polygenic scores and what they can/can’t predict
• 07:03–10:43: How consumers use Orchid, costs involved, user experience (Roshan & Julie’s story)
• 13:25–15:56: Concerns about the accuracy and consistency of these technologies
• 16:09–18:51: Societal unease: eugenics, trait selection, and regulatory gaps
• 19:35–20:40: What do we lose by screening out embryos? The complexity of genetic tradeoffs
• 20:40–23:13: Silicon Valley’s broader motivations and the looming question of inequality

Conclusion

This episode pulls back the curtain on the drive to apply optimization logic to human reproduction, revealing both the promise and the perils. It highlights the collision between Silicon Valley futurism, scientific uncertainty, and haunting social questions, leaving listeners with more questions about where society draws the line between “healthier babies” and a new form of engineered inequality.