Biotech Trends to Watch: Reflecting on the First Half of 2024

If we talk about tech advances in pharma and biotech, the year 2024 has been a blast so far!

Last December I compiled a list of 11 Biopharma Trends to Watch in 2024 and I must say, the actual industry developments in all these areas in the first half of 2024 exceeded my expectations. Both in terms of scientific breakthroughs, and in business activity and financing dynamics (except stock markets which are weird in bio space, as usual).

Now, I’ve decided to review where we stand with some of the trends from my Christmas list half a year later, but today I am mostly focusing on the new trends that I picked to expand the list. So, it would still be relevant to check 11 Biopharma Trends to Watch in 2024 for the complete picture.

2024 is increasingly looking like a potential record breaker when it comes to VC dealmaking, with only the top 50 funding rounds approaching $9 billion (data from a table published by Endpoints News).

‘Organoid Intelligence’

In February 2023, scientists founded a new field: “organoid intelligence” (OI), which I consider one of the potentially most impactful ideas in the biological sciences—for the better or worse.

Led by Dr. Thomas Hartung in the U.S., they are developing biocomputers using brain organoids—lab-grown tissues mimicking organ functions—from human stem cells.

These brain organoids, though not structurally identical to human brains, exhibit neuron-like functions and are envisioned to surpass the computational efficiency of supercomputers, offering novel approaches to pharmaceutical testing and insights into brain functioning.

The field confronts technological challenges like scaling up organoids and developing brain-computer interfaces for data exchange. It also confronts ethical considerations regarding the potential consciousness and rights of these organoids, necessitating a rigorous and inclusive ethical framework for development.

This year we have seen progress by a Swiss biotech startup FinalSpark, which introduced the world's first bioprocessor using 16 human brain organoids.

The platform utilizes four Multi-Electrode Arrays (MEAs) housing the living tissue – 3D cell masses of brain tissue (organoids). Each MEA holds four organoids, interfaced by eight electrodes for both stimulation and recording. Data is transferred via digital analog converters (Intan RHS 32 controller) with a 30kHz sampling frequency and a 16-bit resolution.

In 2023, researchers from Indiana University Bloomington connected their “Brainoware” architecture to an AI tool, and recently, scientists from Tianjin University in China have taken this a step further by creating a robot named MetaBOC with "organoid intelligence" (OI), capable of obstacle avoidance, tracking, and grasping.

The brain-computer interface on a chip technology uses in vitro cultured brain organoids coupled with electrode chips for information interaction through encoding, decoding, and stimulation-feedback, as described by Tianjin University’s Ming Dong. Although brain-powered robots are still a far-future concept, these organoids could help individuals with neurological conditions by potentially being grafted onto living brain tissue to stimulate neuron growth.

The term "Brainoware" was developed by Feng Guo, PhD, at Indiana University Bloomington, and Mingxia Gu, MD, PhD, at Cincinnati Children’s Hospital Medical Center.

It refers to brain-inspired computing hardware utilizing organoid neural networks (ONNs), which are self-organizing brain organoids connected to microelectrode arrays. These ONNs demonstrate unsupervised learning capabilities and hold promise for overcoming current AI hardware limitations, particularly in energy efficiency and processing complexity. The concept and findings were published in the article “Brain organoid reservoir computing for artificial intelligence” in Nature Electronics.

The successes in the field of organoid intelligence are closely dependant on the technological advances in the most vulnerable part of the tech stack: brain computer interfaces, the next item on our list of trends.

Brain Computer Interfaces

Advances in brain computer interface (BCI) technologies are striking, and it is not just Neuralink! Although I would say, the progress of Neuralink is setting the pace for the entire field, with their plans to equip a second patient with the BCI device.

If you would like a high-level but very insightful intro into the field of invasive and non-invasive BCIs, watch my recent interview with Dr. Brian Jamieson, a former NASA engineer turned neuroscience innovator and the founder and CTO of Diagnostic Biochips, a US-based medical devices company: Ex-NASA Expert Unveils Everything You Need to Know About Brain-Computer Interfaces

Invasive BCI technology, led by companies like Neuralink and Blackrock Neurotech, involves surgically implanting electrodes into the brain to capture high-resolution neural signals, providing precise brain-device communication but facing challenges such as infection risks and surgical complexity.

On the other hand, non-invasive BCIs, developed by companies like Kernel, Neurable, BrainCo, Emotiv, and MindMaze, utilize external sensors like EEG and fNIRS to detect neural activity, offering safer and more accessible solutions albeit with lower signal resolution.

Interestingly, China is planning to create a Brain-Computer Interface (BCI) standardization technical committee under the Ministry of Industry and Information Technology (MIIT) to guide industrial standards and promote domestic innovation. This committee aims to develop a BCI standards roadmap and enhance the research and development of key technologies, bolstering China's BCI industry through policy support, financial investment, and the cultivation of domestic and foreign talent.

So, are we witnessing the start of a new global tech race?

‘Gen AI’ and Foundation Models are (Still) on the Rise

As I outlined in ‘11 Biopharma Trends to Watch in 2024’, 2023 was a mixed year for AI in drug discovery. Some notable advancements, including generative AI-enabled successes by Insilico Medicine, were opposed by a number of clinical trial setbacks for AI-inspired drug candidates by other companies, a bit of a cold shower for the AI community.

You may want to check a detailed report by BiopharmaTrend, It’s Been a Decade of AI in the Drug Discovery Race. What’s Next?, if you want to go deeper into pipelines of various companies.

But in general, the media headlines of the first half of 2024 were mostly dominated by the topic of gen AI applications in protein design (e.g. antibodies), and by various companies trying to build large scale general-purpose models for biology, aka ‘foundation models’.

Foundation models represent a new paradigm in artificial intelligence (AI), revolutionizing how machine learning models are developed and deployed. As these models grow increasingly capable, they become useful for applications across a wide range of economic functions and industries, including biotech. Foundation models are a class of large-scale machine learning models, typically based on deep learning architectures such as transformers, that are trained on massive datasets encompassing diverse types of data. The most prominent examples of general-purpose foundation models are the GPT-3 and GPT-4 models, which form the basis of ChatGPT, and BERT, or Bidirectional Encoder Representations from Transformers. These are gigantic models trained on enormous volumes of data, often in a self-supervised or unsupervised manner (without the need for labeled data).

Their scalability in terms of both model size and data volume enables them to capture intricate patterns and dependencies within the data. The pre-training phase of foundation models imparts them with a broad knowledge base, making them highly efficient in few-shot or zero-shot learning scenarios where minimal labeled data is available for specific tasks.

Such companies as Recursion Pharmaceuticals, Bioptimus, Deep Genomics, Ginkgo Bioworks, BioMap, Terray Therapeutics and many others are building foundation models for everything from omics to digital pathology. Read 14 Foundation Models for Biology Research and Chemistry for dive a little deeper.

Another major trend in the AI space is the increasing activity of ‘big tech’ companies, like NVIDIA, Google and others. The numbers of pharma and biotech partnerships with big tech are skyrocketing, while companies such as NVIDIA aim for becoming de facto providers of AI infrastructure for drug discovery and biotech: NVIDIA expands BioNeMo platform with new foundation models and microservices for AI-powered Drug Discovery

But we have to be cautious about gen AI, in general. There are known issues, and the future of this trend is vague due too enourmous costs needed to implement technology at scale. For instance, here is a quite surprising report by Goldman Sachs “Gen AI: Too Much Spend, Too Little Benefit?” which casts shadows on the overly excited market.

In Pursuite of Macrocyclic Peptides

Macrocyclic peptides are superior to small molecules and biologics because they effectively bridge the gap between these two drug classes by offering the high selectivity and potency typical of biologics, while also maintaining the cell permeability and oral bioavailability characteristic of small molecules.

This is due to the ability of macrocyclic peptides to adopt conformations that optimize interactions with diverse protein surfaces, enhancing their efficacy against complex protein-protein interactions. Additionally, macrocycles exhibit improved metabolic stability and can cross biological membranes more effectively than many large biologic molecules, making them suitable for oral administration and intracellular targets. This combination of properties makes them particularly valuable in addressing previously "undruggable" targets, such as certain cancer and infectious disease mechanisms​

The field of macrocycle drug discovery is rapidly advancing, propelled by cutting-edge technologies and innovative approaches from companies like Unnatural Products, Orbis Medicines, Circle Pharma, Insamo, Nimble Therapeutics and others.

Some further reading: The Rise of Cyclic Peptides: Bridging the Gap in Modern Medicine

A Booming Weight-Loss Drug Discovery Landscape at a Glance

In 1986, Danish scientist Jens Juul Holst discovered that the gut hormone GLP-1 stimulates insulin and suppresses appetite. This research led to the development of two blockbuster weight-loss drugs: Wegovy by Novo Nordisk and Zepbound by Eli Lilly, now prescribed to millions as obesity affects 1 in 8 people globally.

Since Wegovy's 2021 launch and Zepbound's approval five months ago, Novo Nordisk and Eli Lilly are leading the next generation of weight-loss drugs, targeting a market projected to reach $150bn by 2030. Currently, 232 anti-obesity drugs are in development, with the most advanced utilizing GLP-1 combined with other hormones.

Novo Nordisk and Eli Lilly, who initially received approval for GLP-1 treatments for diabetes in 2005 and 2010, respectively, are now advancing five new weight-loss drugs in phase 3 trials. Novo Nordisk's CagriSema, targeting over 20% weight loss, and Eli Lilly's retatrutide, showing a 24% weight reduction in early trials, are notable candidates.

Novo Nordisk is also developing amycretin, a promising pill combining GLP-1 and amylin. Analysts like Emily Field from Barclays note these companies continually set higher standards.

Read an overview of this space in our recent newsletter: A Booming Weight-Loss Drug Discovery Landscape at a Glance

A Bang Year for Cell and Gene Therapies

2024 is on track to be a notable year for cell and gene therapy approvals with 6 therapies having scored the approvals since the beginning of the year till now (July).

The FDA has recently approved ELEVIDYS, a gene therapy developed by Sarepta Therapeutics, for Duchenne Muscular Dystrophy (DMD) patients aged 4 and older. This approval marks a significant milestone in the treatment of DMD.

In April, Pfizer has received FDA approval for Beqvez, a hemophilia B gene therapy, and will charge $3.5 million per dose, matching the price of CSL and uniQure's Hemgenix. The treatment aims to reduce the need for frequent and costly intravenous transfusions, offering significant potential long-term healthcare savings. Pfizer will also offer a warranty program to provide financial protections against efficacy failure.

Earlier in March, U.S. FDA approved Bristol Myers Squibb’s Breyanzi ® as the first and only CAR T cell therapy for adults with relapsed or refractory chronic lymphocytic leukemia (CLL) or small lymphocytic lymphoma (SLL).

FDA also approved BMS and J&J CAR-T Cell Therapies for the Earlier Treatment of Multiple Myeloma, and so on (write in the comments if you want me cover this topic in more details).

Looking ahead, 7 more approvals are anticipated within the next six months. This indicates a period of rapid advancement in the cell and gene therapy field. Regulatory approval does not immediately translate into therapies accessible to patients.

It is important to note that regulatory approval is only the initial step. Following approval, several key processes must be addressed, including patient logistics, new medical coverage policies, logistics for treatment delivery, development of new treatment protocols etc.

Amidst the growing trend, the radiopharmaceutical sector faces significant supply chain difficulties, with limited global suppliers for Ac225. This has led to heightened demand and competition for securing isotope supplies.

A Growing Race to Change Status Quo in the Lucrative NGS Market

The next-generation sequencing (NGS) industry is entering an exciting phase, marked by a surge of innovations and competitive dynamics. Over the past three years, several companies have introduced groundbreaking sequencing technologies, challenging the long-standing dominance of Illumina. As we move through 2024, it will be fascinating to see how customers respond to these emerging alternatives.

For instance, Element Biosciences has raised over $277 million in a Series D funding round to further develop and commercialize its DNA sequencing and multi-omics technologies.

The new capital will support the expansion of Element Biosciences' global customer base and the advancement of its technological offerings. Central to these efforts is the AVITI™ benchtop DNA sequencer, which has been rapidly adopted since its release. Additionally, the company plans to launch AVITI24™, an instrument designed to integrate sequencing with cyto-profiling. This technology allows for the simultaneous examination of DNA, RNA, proteins, phosphoproteins, and cell structure within single cells, offering researchers comprehensive insights into biological systems.

PacBio, another major player, introduced the Onso benchtop short-read sequencing platform in October 2022. Recently, PacBio launched the HiFi Prep Kit 96 and HiFi Plex Prep Kit 96, which streamline long-read sequencing workflows, reduce costs by 40%, and cut preparation time by 60%. These kits support running 1,536 samples in a single Revio run. PacBio’s revenue for 2023 surged by 56% to $200.521 million, though the company still reported a net loss of $306.735 million.

Singular Genomics, a relative newcomer, rolled out the G4 Sequencing Platform in late 2021 and recently upgraded it to the G4X™ Spatial Sequencer. This high-throughput platform supports simultaneous direct RNA sequencing, targeted transcriptomics, proteomics, and fluorescent analysis from formalin-fixed, paraffin-embedded tissues. The new F4 Flow Cell aims to double the sequencer’s run output, providing 600 million to 800 million paired reads per flow cell.

MGI Tech, through its U.S. subsidiary Complete Genomics, has also made headlines. Eurofins Genomics ordered MGI’s DNBSEQ-T20×2 (T20) ultra-high throughput sequencer, which is designed to reduce sequencing costs to below $100 per genome. MGI Tech ended 2023 with a net loss of RMB 597.1 million, influenced by China's sluggish economy.

Oxford Nanopore Technologies introduced the PromethION 2 Integrated (P2i) device, facilitating real-time base calling and post-run analysis within the device itself. The company has achieved a record median simplex single molecule accuracy of Q28 (99.8%). Despite a net loss of £154.5 million in 2023, Oxford Nanopore saw underlying revenue grow by 39%, reaching £149.7 million.

Thermo Fisher Scientific continues to innovate within the NGS market under the Ion Torrent brand. The company launched new tools for preimplantation genetic testing-aneuploidy (PGT-A) and cancer testing. Thermo Fisher’s sequencing business, part of its Life Sciences Solutions segment, generated $9.977 billion of the company’s $42.86 billion revenue in 2023.

Ultima Genomics has introduced the UG 100 system, featuring an ultra-high-throughput sequencing architecture with an open silicon wafer and 24/7 run automation. The UG 100 aims to break the $100 genome barrier, offering high accuracy for various applications, including somatic and rare event detection. Ultima raised approximately $600 million upon emerging from stealth in 2022.

The sequencing industry also includes key providers of workflow solutions. Agilent Technologies focuses on sample preparation chemistries and quality control for NGS samples, with its genomics business valued at $500 million. QIAGEN’s Genomics/NGS business grew by 6% in 2023, reaching $239 million. Roche, investing significantly in sequencing, saw its Diagnostics Division generate CHF 14.1 billion ($16.1 billion) in revenue last year.

Topics: Industry Trends