Target Audience
- Entrepreneurs looking to build new businesses using affordable access to DNA sequences, DNA methylation and other chemical modifications, and RNA molecular data.
- Innovators interested in understanding how Oxford Nanopore Technologies has evolved, how it differs from conventional DNA sequencing technologies, and what opportunities it creates for molecular analysis services.
- Founders and technology developers exploring how biosensors, artificial intelligence, and molecular measurement technologies can enable new business models.
Executive Summary
- Oxford Nanopore Technologies (ONT) began providing its compact MinION DNA sequencer to researchers in 2014 and commercialized it in 2015. Over approximately 12 years, the company has dramatically improved sequencing accuracy, speed, and throughput.
- Early read accuracy was approximately 80–90%. Today, single-read accuracy can exceed 99%, while Duplex sequencing, which combines information from both DNA strands, can achieve accuracy above 99.9%.
- Beyond DNA sequences, nanopore technology can now analyze chemical modifications such as DNA methylation, native RNA molecules, and RNA modifications, significantly expanding the information obtainable from individual molecules.
- These advances have been driven by continuous improvements in nanopore proteins, motor enzymes, electronics, and AI. However, challenges remain in insertion and deletion detection, sample preparation, cost, and clinical quality assurance.
- ONT is evolving from a DNA sequencing device manufacturer into a platform for integrated DNA, RNA, and epigenomic analysis, creating opportunities for entrepreneurs building businesses around molecular information.
1. A Technological Revolution That Began with a Pocket-Sized DNA Sequencer
Oxford Nanopore Technologies (ONT), a British biotechnology company, began providing its MinION DNA sequencer, approximately the size of a USB flash drive, to researchers in 2014 and commercialized it in 2015. [1]
Approximately 12 years later, as of 2026, the technology has advanced dramatically.
What makes this evolution particularly interesting is that ONT has achieved substantial improvements in practical performance without fundamentally changing its original operating principle.
Instead, the company has combined advances in protein engineering, enzyme engineering, semiconductor electronics, and artificial intelligence.
Five major advances stand out.
- Sequencing accuracy: Accuracy has improved from approximately 80–90% in the early days to over 99% for individual DNA reads and over 99.9% when information from both DNA strands is combined.
- Sequencing speed and throughput: The speed at which DNA passes through an individual nanopore has increased approximately tenfold, while parallel operation of numerous nanopores has enabled large-scale genome analysis.
- Long-read sequencing: Continuous sequencing of tens to hundreds of thousands of bases has become routine, with reads exceeding one million bases possible under favorable conditions.
- Types of information obtained: The technology can now analyze not only DNA sequences but also chemical modifications such as methylation and native RNA molecules.
- Range of applications: ONT has expanded from portable field sequencers to large instruments capable of analyzing numerous human genomes, as well as applications in clinical testing.
However, not every problem has been solved.
Challenges remain in accurately sequencing regions containing repeated identical bases, detecting low-frequency variants, preparing samples, and ensuring reproducibility. [2]
2. What Does a Nanopore Sequencer Actually Measure?
The fundamental principle behind ONT's technology is relatively straightforward.
A DNA molecule passes through a protein-based nanopore, and changes in the electrical signal are used to determine its sequence.
More precisely, the instrument measures changes in ionic current flowing through the protein nanopore when a voltage is applied across a membrane.
2.1. Multiple Bases Influence the Electrical Current Simultaneously
An important point is that the instrument does not simply identify one nucleotide at a time.
Typically, multiple bases located within the narrow region of the nanopore influence the measured ionic current simultaneously.
Therefore, the DNA sequence must be inferred from the resulting electrical signal.
For example, consider a DNA molecule with the following sequence:
… A C G T T A G C …At each moment, the measured current depends on the combination of several nucleotides occupying the nanopore.
A motor protein, or enzyme, is used to control the movement of the DNA molecule through the pore.
2.2. Three Fundamental Challenges of Early Nanopore Sequencing
From the beginning, this approach faced three major technical challenges.
- Overlapping signals: Because several bases influence the current simultaneously, different DNA sequences can produce similar electrical signals.
- Variable DNA movement: Fluctuations in the speed of DNA translocation make it difficult to accurately associate electrical signals with individual bases.
- Signal variability and noise: Nanopore conditions, electrical noise, and DNA sample quality can cause different current patterns even when the underlying DNA sequence is identical.
Much of ONT's technological development over the following decade has focused on reducing these problems.
3. The Evolution of Nanopore Technology from 2014 to 2026
ONT has continuously improved nanopore structures, DNA motor enzymes, signal-processing algorithms, and sequencing instruments. [1][2]
The major milestones can be summarized as follows.
| Period | Major Technological Development | Challenges Addressed |
|---|---|---|
| 2014 | Introduction of MinION: From proof of concept to practical use | Enabled portable, real-time, long-read sequencing, although accuracy, output, and batch-to-batch variability remained significant challenges |
| 2016–2018 | R9 generation: Improvements in nanopores and motor enzymes | DNA translocation speeds reached approximately 400–450 bases per second. AI-based basecalling improved accuracy and throughput |
| 2019–2020 | R10 generation: Improved signal resolution | Nanopore structures were redesigned to better distinguish similar nucleotide sequences and repetitive regions |
| 2021–2023 | Q20+, R10.4.1, and Kit 14: A turning point in accuracy | Single-strand read accuracy exceeded 99%. Duplex sequencing matured, enabling accuracy above 99.9% |
| 2024–2025 | Maturation of large-scale genome analysis and clinical applications | Advances in high-accuracy AI analysis, methylation detection, ultra-long reads, and high-throughput instruments. MinION Mk1D was introduced |
| 2026 | Toward an integrated platform for DNA, RNA, and epigenomic analysis | Improvements in PromethION Plus flow cells, workflows, AI analysis, and quality control. Peptide and protein sequencing remained under development |
These are representative milestones, and actual performance varies depending on sequencing conditions. [1][3]
The important lesson is that ONT did not begin with a fully developed, highly accurate sensor.
Instead, it gradually transformed the technology into a practical analytical platform by improving multiple components over many years.
4. The Most Important Advance: How Sequencing Accuracy Improved
One of ONT's most significant achievements has been the dramatic improvement in sequencing accuracy.
This progress can be divided into four major areas of technological development.
4.1. Engineering Better Nanopore Proteins
ONT has improved the protein nanopores used to detect DNA, progressing from early R7 designs through R9 and R10.
In particular, the R10 generation introduced improvements to the constriction structures inside the nanopore, allowing electrical signals associated with different positions along the DNA molecule to be distinguished more effectively.
In electronics terminology, this is analogous to improving sensor resolution and the signal-to-noise ratio.
4.2. Improving the Motor Enzymes That Control DNA Movement
If DNA were simply pulled through a nanopore by an applied voltage, it would move too quickly for accurate nucleotide identification.
To solve this problem, ONT has continuously improved motor proteins that regulate DNA movement.
Representative DNA translocation speeds for different technology generations are shown below.
| Generation / Period | DNA Translocation Speed |
|---|---|
| Early 2014 technology | Approximately 30 bases/second |
| 2015 | Approximately 70 bases/second |
| R9 in 2016 | Approximately 250 bases/second |
| R9.4 and later | Approximately 450 bases/second |
These are representative published values from different chemistries and operating conditions. [1]
Faster controlled movement increased the amount of DNA that could be sequenced per unit of time.
At the same time, improvements in movement control helped stabilize the electrical signals needed for accurate base identification.
4.3. Introducing AI to Interpret Electrical Signals
This is arguably one of the most important developments.
Early basecalling methods, which convert electrical signals into nucleotide sequences, relied on statistical techniques such as hidden Markov models.
Over time, neural-network-based approaches became increasingly important.
Today, deep-learning-based basecallers such as Dorado are used to interpret nanopore signals.
For example, when a similar electrical signal continues over time, the algorithm must determine whether:
- Several identical nucleotides are present consecutively.
- DNA movement has temporarily slowed.
- Electrical noise has affected the measurement.
Modern AI models can use surrounding signal patterns to distinguish among these possibilities.
In other words, ONT did not improve only the physical sensor. It also increased the amount of useful information that could be extracted from the same type of sensor signal.
4.4. Using Both DNA Strands to Correct Errors
DNA consists of two complementary strands.
If both strands can be sequenced, information from one strand can help correct errors made while reading the other.
This is the principle behind Duplex sequencing.
The distinction between the two approaches is straightforward.
- Simplex sequencing: Determines the DNA sequence using information from one strand.
- Duplex sequencing: Combines information obtained from both complementary strands to improve accuracy.
If a sequencing error occurs in one strand, the information from the complementary strand can help resolve it.
Sequencing accuracy is often expressed using Phred quality scores.
A Q20 score corresponds to an expected error probability of 1%, while Q30 corresponds to 0.1%.
| Sequencing Method | Representative Accuracy | Expected Error Rate |
|---|---|---|
| Early MinION | Approximately 80–90% | Approximately 10–20% |
| Current-generation Simplex | Over 99% (Q20+) | Below 1% |
| High-accuracy Duplex | Over 99.9% (Q30+) | Below 0.1% |
These values represent different technology generations and sequencing conditions. [2]
The proportion of DNA molecules successfully analyzed using Duplex sequencing depends on experimental conditions, and not all sequencing data achieve Q30 or higher.
It is also important to distinguish the accuracy of an individual molecular read from the accuracy of a consensus sequence generated by combining multiple reads.
5. Increasing Throughput and Expanding the Instrument Portfolio
ONT's product lineup is no longer limited to the compact MinION.
The company now offers instruments ranging from portable sequencing devices to large systems designed for major research facilities.
All are based on essentially the same nanopore sequencing principle.
5.1. MinION Mk1D: Portable Sequencing
The MinION Mk1D represents a newer generation of the original portable sequencer.
Introduced in 2024, it includes improvements in temperature control and durability.
It can be used for applications such as infectious disease analysis and environmental DNA sequencing in field settings.
5.2. GridION: Processing Multiple Samples in the Laboratory
GridION can operate multiple MinION-type flow cells in parallel.
It is designed for laboratory environments where researchers need to process multiple samples and integrate sequencing with computational analysis.
5.3. PromethION P48: Large-Scale Genome Analysis
PromethION P48 is a high-throughput instrument capable of operating up to 48 high-density flow cells.
It supports terabase-scale data generation in a single sequencing run and can be used for large research projects and the analysis of numerous human genomes.
5.4. Approximately 40-Fold Growth in MinION Data Output
According to ONT's 2025 annual report, MinION data output increased approximately 40-fold over a decade, while sequencing accuracy improved to over 99%. [1]
An important point is that the original MinION was not simply a small sequencing instrument.
It was the starting point for a scalable technology platform that could eventually support both portable instruments and large-scale sequencing systems.
6. Beyond DNA Sequences: Reading Methylation and RNA
This is one of the most distinctive advantages of nanopore sequencing.
In conventional DNA sequencing workflows, DNA molecules are often chemically or enzymatically processed before their sequences are determined.
As a result, information about chemical modifications on the original DNA molecules may be lost, or additional analytical methods may be required.
Nanopore sequencing offers a different approach.
Modified nucleotides can generate electrical signals that differ from those produced by unmodified nucleotides.
By analyzing these differences, it becomes possible to extract multiple types of molecular information.
| Type of Information | What Nanopore Technology Can Analyze |
|---|---|
| DNA sequence | Single-nucleotide polymorphisms (SNPs), insertions, deletions, and structural variants |
| DNA methylation | CpG methylation and other modifications on the same DNA molecules used for sequence analysis |
| Ultra-long DNA | Complex repetitive regions, chromosome structure, and haplotypes |
| RNA sequence | Native RNA molecules without conversion into cDNA |
| RNA modifications | Chemical modifications such as m6A |
| Peptides | Amino acid sequence identification technologies currently under research and development |
6.1. Analyzing DNA Sequences and Methylation Simultaneously
The ability to analyze DNA sequences and methylation patterns from the same individual molecule is particularly important for cancer research and epigenomics.
It allows researchers to examine not only the nucleotide sequence but also chemical modifications associated with that same DNA molecule.
6.2. Direct RNA Sequencing
ONT can read RNA molecules directly without first converting them into complementary DNA (cDNA).
Direct RNA sequencing makes it possible to examine RNA isoforms and chemical modifications while avoiding biases introduced by reverse transcription and PCR.
However, RNA sequencing remains more sensitive to sample quality and can be less accurate than DNA sequencing.
The maturity of RNA modification detection also varies depending on the modification being analyzed.
6.3. Adaptive Sampling: Deciding What to Sequence While Sequencing
Another interesting development is the continued evolution of Adaptive Sampling, including advances announced in 2026. [3]
Adaptive Sampling allows software to begin analyzing a DNA molecule and determine whether its sequence belongs to a region of interest.
If the molecule is not relevant, the system can eject it from the nanopore and begin analyzing another molecule.
This means the sensor no longer simply measures whatever passes through it.
Instead, the instrument can use real-time analytical results to influence which molecules it measures next.
This represents a different kind of advancement from simply increasing sequencing speed.
7. Technical Challenges That Remain in 2026
Despite major improvements in accuracy and throughput, important problems remain unresolved.
The major challenges can be summarized as follows.
| Challenge | Progress Achieved | Remaining Limitations |
|---|---|---|
| Basecalling accuracy | Dramatically improved | Higher single-molecule accuracy and low-frequency variant detection |
| Homopolymer regions | Improved through R10 and AI | Insertion and deletion errors remain |
| Ultra-long DNA sequencing | Substantial progress | Extracting DNA without fragmentation remains critical |
| Throughput and cost | Improved by tens of times or more | Flow cell prices, lifespan, and utilization |
| RNA analysis | Direct RNA sequencing has become practical | Accuracy, throughput, and analytical model limitations compared with DNA |
| Reproducibility and quality assurance | Improvements through products such as Q-Line | Standardization and regulatory requirements for clinical testing |
7.1. Insertions and Deletions Remain Challenging
For example, a comparative study of clinical genome analysis published in 2026 reported that ONT demonstrated strong performance in detecting single-nucleotide substitutions, while insertion and deletion detection remained a relative weakness.
Regions containing repeated identical bases, known as homopolymers, are particularly challenging because it can be difficult to determine the exact number of repeated nucleotides from the electrical signal.
These regions continue to be important targets for technological improvement.
7.2. Sample Preparation Is Critical for Ultra-Long DNA Sequencing
In principle, nanopore sequencing does not impose a strict limit on the length of the DNA molecule being analyzed.
In practice, however, DNA molecules are frequently fragmented during extraction and sample preparation.
Consequently, performance depends not only on the sequencing sensor but also on how the sample is prepared.
Even if the instrument can sequence extremely long DNA molecules, that capability cannot be fully utilized if the DNA has already been broken into short fragments.
7.3. Clinical Applications Require Reproducibility and Quality Assurance
In clinical testing, the ability to improve sequencing accuracy through software updates creates both opportunities and challenges.
Although improved software can enhance performance, each significant software update may require renewed validation of the clinical testing workflow.
ONT's development of quality-controlled Q-Line products is partly intended to address this issue.
Achieving high sequencing accuracy in a research environment and consistently guaranteeing analytical quality in clinical testing are two different requirements.
8. How Does ONT Compare with Illumina and PacBio?
To understand ONT's position, it is useful to compare the technology with other major DNA sequencing platforms.
| Comparison | Illumina | PacBio HiFi | Oxford Nanopore |
|---|---|---|---|
| Sequencing principle | Optical detection during DNA synthesis | Optical detection of single-molecule DNA synthesis | Ionic current measurements through nanopores |
| Typical read length | Short (100–300 bases) | Long (approximately 10–25 kb) | Extremely long reads possible |
| High-accuracy base identification | Strong capability | Strong capability | Greatly improved, but condition-dependent |
| Large structural variant detection | More limited | Strong capability | Particularly strong |
| Native DNA methylation analysis | Usually requires additional methods | Possible | Direct detection alongside DNA sequence |
| Real-time analysis | More limited | More limited | Strong capability |
| Portability | Generally limited | Limited | Strong capability |
This comparison suggests that ONT is not simply trying to replace Illumina.
Its distinctive value lies in the ability to analyze DNA molecules in a relatively native state, preserve long molecular sequences, obtain information about chemical modifications, and generate data in real time.
For entrepreneurs considering businesses based on DNA sequences, chemical modifications, or RNA molecules, it is therefore important to evaluate more than the cost per sequenced base.
The types of molecular information that can be obtained may be just as important.
9. How Has the Nature of the Technology Changed Over 12 Years?
Looking back at ONT's development, three changes are particularly significant.
9.1. From a DNA Sensor to an AI-Integrated Molecular Information System
One major transformation is that nanopore sequencing has evolved from a DNA sensor into a molecular information system integrated with AI.
Even when the electrical signal produced by a nanopore is incomplete or ambiguous, practical sequencing accuracy can be achieved by optimizing protein design, motor enzymes, signal processing, and AI models together.
9.2. From Reading DNA to Reading Multiple Types of Information from Individual Molecules
Nanopore technology can now provide more than nucleotide sequences.
It can also obtain information about methylation, RNA modifications, molecular length, and haplotypes.
This creates the possibility of collecting information through a single analytical platform that previously required multiple technologies.
9.3. From Fixed Instrument Performance to Continuous Improvement Through Software and Consumables
Another important characteristic is that sequencing performance can improve through software and consumable updates, even without replacing the entire instrument.
This reflects the combination of semiconductor technology, protein engineering, and artificial intelligence in a single measurement system.
However, improvements in nanopore structures and motor enzymes still require physical changes.
AI alone cannot overcome every limitation of the underlying measurement technology.
10. Technologies to Watch Over the Next Five to Ten Years: Protein Sequencing
At ONT's technology presentation in May 2026, the company demonstrated progress toward identifying proteins by determining amino acids in peptides. [3]
This does not mean that nanopore-based protein sequencers have reached the same level of commercial maturity as DNA sequencers.
Nevertheless, the development points toward an important possibility.
If variations in ionic current can reveal the nucleotide sequence of DNA, appropriately engineered nanopores and molecular transport mechanisms might also enable the identification of proteins and other molecules through their characteristic electrical signals.
Several challenges are more difficult than those encountered in DNA sequencing.
- Distinguishing among 20 different amino acids.
- Precisely controlling peptide movement through the nanopore.
- Separating the effects of molecular structure and chemical modifications on electrical signals.
Despite these obstacles, ONT's technological direction can be interpreted as a transition from DNA sequencing instruments toward a more general electrical single-molecule information analysis platform.
11. What Does This Mean for Entrepreneurs Building New Businesses?
ONT's evolution has implications beyond improvements in DNA sequencer performance.
It is also relevant for entrepreneurs seeking to build businesses around DNA sequences, methylation and other chemical modifications, and RNA molecular information.
11.1. Lower Costs and Smaller Instruments
From the original MinION to current devices, technological advances have made high-accuracy DNA analysis possible with compact instruments while substantially increasing data throughput.
However, actual analysis costs still depend on factors such as flow cell prices, lifespan, utilization, and sample preparation.
Entrepreneurs therefore need to consider real operating conditions rather than relying only on instrument size or advertised throughput.
11.2. The Value of Obtaining Multiple Types of Molecular Information
The ability to obtain DNA sequences and methylation data from the same molecule, as well as directly sequence RNA, is a significant characteristic of ONT.
These capabilities can be applied to cancer research, epigenomics, RNA isoform analysis, and structural variant detection.
They also create opportunities to obtain molecular information through one platform that previously required multiple analytical technologies.
11.3. Real-Time Analysis and Measurement Control
ONT's ability to generate sequencing data in real time is another important feature.
Adaptive Sampling goes further by using the data already collected to influence which DNA molecules are analyzed next.
This represents a shift from instruments that simply collect data for later analysis toward systems capable of feeding analytical results back into the measurement process.
11.4. Using AI to Increase the Value of Measurement Data
The evolution of ONT has not depended solely on physical improvements to its sensors.
Advances in AI-based signal interpretation have increased the amount of molecular information that can be extracted from electrical measurements.
This provides a useful example for entrepreneurs considering new measurement technologies and businesses that combine biosensors with artificial intelligence.
11.5. Quality Assurance and Reproducibility Matter for Commercialization
A technology that works in a research environment is not necessarily ready to be offered as a consistent clinical testing service.
Challenges remain in sequencing accuracy, low-frequency variant detection, DNA and RNA sample quality, flow cell performance, and validation following software updates.
Entrepreneurs developing molecular information services need to understand these practical limitations.
12. Conclusion: How an Imperfect Biological Sensor Became a Powerful Analytical Platform
Perhaps the most fascinating aspect of ONT's evolution over the past 12 years is that the company did not begin with a perfect sensor.
Instead, it transformed a biological sensor with substantial limitations into a powerful analytical system through continuous improvements in supporting technologies and computational methods.
The original MinION offered a revolutionary ability to sequence long DNA molecules in real time, but it also faced significant limitations in accuracy and throughput.
Over time, advances in nanopore proteins, motor enzymes, electronic circuits, AI-based signal analysis, and Duplex sequencing made high-accuracy DNA analysis and large-scale genome sequencing possible.
The technology has also expanded beyond DNA sequences to include DNA methylation, native RNA molecules, and RNA modifications.
In the future, it may extend to peptides, proteins, and even broader categories of molecular information.
At the same time, important challenges remain in insertion and deletion accuracy, sample preparation, cost, and quality assurance.
Nevertheless, ONT's progress offers valuable lessons not only for biosensors but also for the development of entirely new measurement technologies.
For entrepreneurs building the next generation of biotechnology businesses, nanopore sequencing should be viewed not merely as an improved DNA sequencing method, but as an evolving technological foundation for obtaining molecular information affordably, comprehensively, and in real time.
References
[1] Oxford Nanopore Technologies, “Continuous development and improvement,” Official Technology Overview. https://nanoporetech.com/about/continuous-development-and-improvement
[2] Oxford Nanopore Technologies, “Accuracy,” Official Technical Documentation. https://nanoporetech.com/platform/accuracy
[3] Oxford Nanopore Technologies, “London Calling Technology Update,” 2026. https://nanoporetech.com/ja/news/london-calling-technology-update
[4] Nucleic Acids Research, 2026, DOI: 10.1093/nar/gkag023. https://doi.org/10.1093/nar/gkag023