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In Conversation: Synthetic Biology

Founders Fund2016-11-16
founders fund#science#technology#synthetic biology#utopia#anatomy of next
3K views|7 years ago
💫 Short Summary

The video explores the potential of synthetic biology in extending human life, reverse engineering biological evolution, treating diseases, and enhancing natural capabilities. It discusses reprogramming the immune system to target cancer cells, the development of cancer treatments, CRISPR technology for gene editing, understanding transcriptional logic, the importance of genomic datasets, and the challenges of data access and privacy. Advancements in technology are enabling innovative research in biology, with a focus on understanding cellular processes and potential lifespan increases. The field is progressing towards more targeted and effective treatments through rigorous studies and trials.

✨ Highlights
📊 Transcript
Discussion on synthetic biology and longevity at Founders Fund live stream.
Panel explores potential of engineering cells to extend human life.
Ambitious goal of reverse engineering biological evolution to treat diseases and enhance capabilities.
Exciting possibilities of synthetic biology, like creating armored suits that respond to pressure.
Panelists share experiences and emphasize innovation in the field.
Synthetic biology aims to revolutionize disease treatment by creating living, programmable systems.
The focus is on addressing metabolic problems like blood sugar and insulin imbalance with dynamic tools.
Traditional static treatments with simple molecules have been ineffective in managing these complex conditions.
Researchers are working towards developing dynamic cells to better address the dynamic nature of diseases.
Reprogramming the human immune system to target diseases like cancer.
T-cells are being engineered to detect foreign antigens on cancer cells and destroy them.
Designing receptors to bind to antigens on cancer cells to enhance the immune system's response.
Accelerating the immune system's ability to fight cancer effectively.
Developing innovative strategies to improve cancer treatment outcomes by bypassing the natural immune response process.
Overview of synthetic biology and its applications in biotechnology.
Synthetic biology has evolved since the 1980s, with a focus on manipulating DNA to produce proteins and antibodies.
Cancer treatments have been developed through synthetic biology, targeting cancer cells and creating effective binders for cancer molecules.
The concept of 'ancillary synthetic biology' involves processes occurring in a dish before being introduced into the body.
Synthetic biology shows great potential in various medical applications, showcasing advancements in the field.
Advancements in biology technology, particularly CRISPR, have led to a surge of biology companies in Silicon Valley.
CRISPR technology allows for precise gene editing, targeting specific mutations without harming surrounding genes.
The potential of CRISPR in treating genetic diseases such as cystic fibrosis is emphasized.
The conversation explores the importance of CRISPR and its implications for gene editing techniques.
CRISPR technology allows for precise targeting of genes for editing, with potential to solve genetic disorders like cystic fibrosis.
Challenges exist in improving accuracy and delivery methods, including packaging CRISPR with viral technologies.
The technology is still in progress and requires further development for widespread success in gene editing applications.
Research focus on transcriptional logic and gene expression patterns in development.
Human genome complexity poses challenges in decoding non-coding regions that encode developmental instructions.
Advanced microscopy techniques enable detailed study of single cell development into complex organisms.
Regulatory logic governing gene expression and body plan formation remains largely unknown.
Importance of large datasets in genomics research.
Thousands to tens of thousands of genomes needed for meaningful analysis.
Around a million fully sequenced genomes globally, with varying accessibility.
Challenges of data access and potential for machine learning applications in genomics discussed.
Emphasis on the need for more extensive datasets to advance research in the field.
The importance of using basic image recognition nets in biology for state-of-the-art results.
Researchers in machine learning are hesitant to access data due to challenges in obtaining it, despite the benefits of open data sharing.
Concerns raised about insurance companies using genetic data for decision-making, emphasizing caution in sharing genetic information online.
The significance of combining genomic applications with basic lab tests for a comprehensive understanding of health and genetic predispositions.
Importance of data access and privacy in developing machine learning models for healthcare.
Cultural value of privacy and the need for policy systems aligned with these values.
Challenge of justifying data exploration for tangible benefits in healthcare.
Necessity of encoding benefits abstractly to create a policy framework benefiting all, including those in databases.
Significance of developing technical systems for secure communication in healthcare research.
Challenges in Centralized Data Storage and Sharing in the US.
Cultural and governmental factors in the US have led to a lack of centralized approach to data storage and sharing.
Preferential treatment and coordination issues are concerns hindering progress towards a unified system.
Advancements in genomics have not met the expectation of immediate cures for diseases post-genome sequencing.
Skepticism and challenges exist in promoting new technologies like CRISPR therapeutics.
Challenges in understanding genetic code.
Genetic code is complex and non-deterministic, unlike computer code, making it difficult to decipher.
Interactions between proteins and statistical nature of cellular processes add to the challenge of predicting outcomes based on genetic code.
Conducting experiments is essential for gaining insights into how genetic code functions.
Understanding biological systems presents a deeper problem in comprehending genetic code.
Advancements in technology have revolutionized biological research.
Improved computers and imaging sensors facilitate the processing of large data sets.
Cheap sequencers and powerful GPUs enable efficient data analysis and pattern recognition.
Future technology may allow for direct protein sequencing and rapid cell surveys.
The intersection of technology and biology is leading to new perspectives and opportunities for innovation in research.
Advancements in biology are rapidly progressing with the use of new technologies like lenses for more reliable data.
Research is focused on understanding cell processes and making predictable changes for potential lifespan increases.
Companies are funding studies targeting pathways related to aging, with hopes for therapies affecting lifespan already in the clinic.
The approach to biology is shifting towards a more systemic view, leading to exciting possibilities and optimism for the future of medicine and biology.
The importance of advancements in biology and medicine in conducting double-blind studies and trials.
Double-blind studies allow for a deeper understanding of physiology and anatomy, focusing on desired outcomes.
Progress in the field is moving towards understanding from first principles, leading to more targeted and effective treatments.