Good day, and thank you for standing by. Welcome to GenScript Biotech 2026 interim results conference call. At this time, all participants are in listen-only mode. After the speakers' presentation, there will be a question-a nd- answer session. To ask a question during the session, you need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, CFO of GenScript Biotech Corporation, Mr. Phil Zhou. Please go ahead. CFO at GenScript. Welcome to our 2026 Interim Results Conference Call. Joining me on the call today are Mr. Robin Meng, Chairman of the Board, Ms. Sherry Shao, Rotating CEO of GenScript, Dr. Ray Chen, President of GenScript Life Science Group, Dr. Aixi Bai, General Manager of Bestzyme, and Mr. Allen Guo, CEO of ProBio. During today's call, we will be making statements about future expectations, plans, and prospects as well as any other statements regarding matters that are not historical facts, which may constitute forward-looking statements. Actual results may differ materially from those indicated by such forward-looking statements because of various important risk factors and changing market conditions. We do not undertake any obligation to publicly update any forward-looking statements. Before we begin, please note that the prior period figures presented in this conference call are on a comparable basis, excluding the financial impact of the license transaction with LaNova Medicines pursuant to the license agreement that was recognized in the prior period. We believe this provides a more objective view of the group's underlying business performance. Today, Sherry will provide an overview of our company performance and growth drivers. I will then guide you through the financial performance. Following that, Sherry will update on our full-year guidance. We will also have a Q&A session at the end of the call. As a reminder, today's presentation and recordings will be available in the investor relations section of the company's website. Now, I will hand it over to Sherry. Thank you, Phil. Before turning to company performance, I would like to provide an overview of our company and the core drivers behind our long-term growth. GenScript is a leading global platform for life science services and products. We serve more than 260,000 customers across over 100 countries and regions, supported by an integrated R&D, manufacturing, and commercial network across North America, Europe, and Asia Pacific. In the first half of 2026, GenScript delivered a strong set of results that demonstrate both growth, momentum, and improving business quality. Revenue exceeded $400 million with 27.3% year-over-year growth, while adjusted net profit reached $62.5 million, growing more than 200% year-over-year. More importantly, these results reflect the early benefits of a more scalable growth model. AI-driven demand is expanding our addressable opportunities. Our gene-to-protein platform is deepening customer value and competitive modes. Operating leverage is translating growth into stronger profitability. Now, let me walk you through key operational highlights across our business for the first half. First, our Life Science Group scaled up high-quality growth. Powered by growing AIDD demand, we achieved both growth at scale and margin improvement. We have further enhanced global delivery, with about 60% of our labs equipped with AI-driven automated workstations, lifting operational efficiency and productivity at scale. Importantly, our gene-to-protein platform continued to change the game by compressing turnaround from digital sequence to model-ready data to as fast as four days, the fastest turnaround in the industry. This is precisely the kind of speed the AI era demands. ProBio maintains steady growth with accelerating order momentum. Increasing pipelines moving to downstream, driven by AI and in vivo CAR-T is becoming a new growth engine, while improving scale continues to lift profitability. For Bestzyme, rising customer adoption continues to validate the commercial value of our products. We are also applying AI to protein design and engineering to accelerate innovations and their launch in the market with impact. Our growing IP portfolio underpins our long-term successes. As we look ahead, AI is revolutionizing drug discovery. I will highlight how these disruptive trends in AI drug discovery are unfolding, and why GenScript is perfectly positioned to leverage this shift and drive this revolution forward. AIDD is approaching a critical tipping point, as summarized by [Azorobic's] briefing. Over the past few years, AI has fundamentally reshaped the software development industry, and life sciences is emerging as the next high-value application beyond software. We see increasing AI applications in target delivery, molecule design, and candidate selection. According to another survey by Deloitte, nearly 60% of surveyed biopharma leaders ranked AI in research and discovery as a top priority. Indeed, the potentials of AI in drug discovery is undeniable. First, AI has the potential to dramatically accelerate early-stage discovery, compressing a traditional four to six-year timeline into just 12- 18 months. Second, AI can enable researchers to explore a much broader range of therapeutic targets, modalities, and molecule designs at computational scale. Third, by identifying high-quality winning candidates early before more costly downstream development begins. Ultimately, AIDD models promise higher success rates and a maximized ROI. Here is the structural shift we are tracking. Applying AI to the life sciences and drug discovery is fundamentally more complex than pure tech. Biological data is inherently more complicated, and our feedback loops demand rigorous physical wet lab experiments. But make no mistake, the AI-driven transformation of our industry is inevitable. Those who can bridge the gap between digital design and wet lab truths will dominate the market. The key challenge facing AI-driven drug discovery today is no longer generating ideas and designs. It is validating them. AI models can now generate thousands of candidate molecules in hours. However, traditional experimental workflows were not designed for that scale of speed. Validation often takes weeks, involves multiple disconnected steps, and produces data that is not always ready to feed directly back into AI models. As AI accelerates design, the bottleneck is shifting decisively toward experimental validation. We are experiencing a significant opportunity emerging around a new category of infrastructure: validation platforms that are fast enough for AI iteration, scalable enough for AI volume, and structured for continuous model learning. That is where GenScript is uniquely positioned. We are here to close the loop. To address this industry challenge, we put toward our 4D AI to biology validation engine. This is an integrated validation platform built specifically for the AI, and it will continue to improve and evolve. Our platform combines four critical capabilities. First, scalable capacity. Our modular gene-to-protein and assay workstations allow us to rapidly add throughput as customer demand grows. Second, speed. We can move from digital sequence to model-ready biological data in as short as four days, dramatically reducing validation timelines. This is industry-leading, world-leading. Third, iterative execution. Automated and digitally-abstracted workflows reduce manual handovers. Then improve consistency and scale efficiency. Fourth, AI-ready data. Results are generated in formats that can support model iteration and continuous learning. Together, these capabilities allow GenScript to help close the gap between digital intelligence and biological execution, transforming validation from an industry bottleneck into a next-generation solution and our competitive advantage. Here's why this matters commercially. This shift isn't just technological. It's redefining our customer base and our revenue model. AI is changing who buys from us and how they buy. Beyond our core pharma and biotech base, we are now increasingly engaging AI-native biotechs, model developers, and major technology companies entering life sciences for the first time. A genuinely new commercial category for life sciences industry and for GenScript. AIDD is changing how our customers operate. Their AI models generate more designs, run more experiments, and iterate faster, which turns validation from a one-off and a longer cycle project into a recurring, ongoing stream of demand. That shifts the new segment of customers and evolving operating models from our customers. It's what makes this opportunity structurally larger than a typical cycle. The result is threefold: a larger customer universe, higher order volume, faster cycles, and deeper, longer-term engagement. Together, they create a larger and more strategic growth opportunity for GenScript over time. For investors who are newer to the AI for science ecosystem, this slide illustrates where GenScript sits in the value chain. AI models can generate designs, but those designs must ultimately be translated into biological constructs, validated experimentally, developed into candidates, and ultimately manufactured at scale. GenScript participates across multiple points of that workflow. Our Life Science Group leads validation through our gene-to-protein and assay platform at an unmatchable speed and scale. We are closely integrated into the AIDD group. ProBio helps advance promising candidates into development and manufacturing once pipeline advances. Bestzyme leverages innovation and AI-enabled protein engineering to create new opportunities in synthetic biology. Combined with our global operating footprint and strong balance sheet, these capabilities position GenScript as a critical infrastructure provider, supporting the next generation of AI-enabled biotech innovation. We're not simply participating in AI for science ecosystem. We are actively building the validation infrastructure that enables it. As AI-driven discovery scales, GenScript will continue to strengthen its position as one of the most strategic and valuable points in the biotechnology value chain. Having discussed the strategic drivers shaping our long-term opportunity, I will now hand the call over to Phil to reveal our finance performance in greater detail. Thank you, Sherry. Let me now take you through the group's financial performance for the first half. Revenue reached $404.2 million, up 27.3% year-over-year, reflecting strong momentum across the group. Growth was broad-based. Life Science Service and products grew 28.8% to $319 million. ProBio grew 34.2% to $61.1 million, and Bestzyme grew 7.4% to $30.4 million. Alongside the top-line growth, we also delivered higher quality earnings. Group gross profit reached $206.7 million, up 48% year-over-year, significantly outpacing revenue growth. This reflects our improved business mix, operational efficiency, and scale benefits. Benefiting from revenue growth and improved operating leverage, adjusted net profit reached $62.5 million, up 203.3% year-over-year, a record for any half, and clear evidence that profitability is scaling faster than the top line. Overall, the group delivered growth across revenue, gross profit, and net profit, which is a strong validation of our ability to create long-term value by leveraging our global footprints, innovative platforms, and scale. Now, let's turn to the Life Science Group, or LSG. In the first half, LSG delivered strong revenue growth alongside a meaningful profit expansion and operational efficiency gains. Revenue reached $319 million, up 28.8% year-over-year, around 10 percentage points above initial guidance. Growth was driven by sustained global customer demand, increased penetration of gene-to-protein platform, and rapid expansion in AIDD-related demand. We are seeing strong demand for high-quality gene synthesis, protein expression, and related research services across pharma and biotech customers and AI-driven companies. More importantly, profitability improved significantly. Adjusted gross profit reached $185 million, up 46.1% year-over-year. Adjusted operating profit reached $94 million, up 102.8%, surpassing $90 million for the first half, and effectively doubling. This benefits from our improved operating leverage. Over the past couple of years, we have consistently invested in automation, digital operations, capacity expansion, and our global footprints. Alongside business growth, we see higher operational efficiency and stronger profitability, enabling profit growth to outpace revenue growth. Expense trends were also encouraging. Growth in selling, administrative, and R&D expenses remained below revenue growth, reflecting strengthening scale effects and disciplined resource allocation. We also see improved margins. In the first half, adjusted gross margin reached 57.8%, or 55.4%, excluding the impact of U.S. tariff refunds. Adjusted operating margin reached 29.5%, or 27.1% on the same basis, both improved significantly compared to first half 2025. The operating margin approaching 30% marks an important milestone for LSG, transitioning from investment to growth at scale and profitability. With growing demand from AI-driven Drug Discovery and expanding global customer base and increasing platform synergies, we believe LSG is well-positioned to drive both revenue growth and profitability improvement. This slide shows why LSG's growth is not dependent on single product, region, or customer type. LSG's sustainable growth is attributable to its leading platforms, global reach, and broad customer base. Looking first at our product mix, gene-to-protein products and services contributed around two-thirds of LSG revenue, making it our most important business area. This reflects both our leadership of gene-to-protein platform and strong customer demand for integrated R&D solutions. By region, our revenue base remains well-balanced. North America contributed approximately 50% of revenue, while Asia Pacific and Europe accounted for 29% and 21% respectively. This diversified global footprint allows to capture opportunities across major markets while enhancing our business resilience. Our revenue stream is highly resilient and built on a strategically diversified customer base. With over 80% of revenue generated by pharma and biotech, we are deeply embedded in leading R&D engines. Complementing this, our robust presence across global research institutions ensures long-term structural collaboration well beyond our industry segments. Taken together, our gene-to-protein platform, global operating network, and diversified customer base provide a strong foundation for LSG's continued growth, enabling us to capture opportunities arising from AI-driven life science innovation. Moving on to the opportunities ahead and the key drivers that will support long-term growth. We see three engines powering LSG's growth in the years ahead. First, our integrated gene-to-protein platform remains the primary engine of our growth. We are tracking the structural shift as customers transition from transactional single-product purchases to our comprehensive end-to-end solutions. This transition embeds us deeper into their R&D workflows, accelerating top-line revenue, while directly driving margin expansion and long-term profitability. Second, AI-driven demand has rapidly emerged as a massive new growth engine. Unlike traditional discovery, AIDD programs require exponentially higher throughput, continuous engagement, and long-term collaboration. For GenScript, this translates directly into significantly larger contract values and exceptional long-term value, long-term revenue visibility. We expect this momentum to compound aggressively with AIDD orders projected to double in the second half and maintain that hyper growth trajectory over the next several years. Third, we are seeing stronger returns from our platform investments. The foundational investments we've made in automation and digital capacity are now highly accretive. Driven by climbing utilization rates, our gene-to-protein platform ROIs surged 1.5 times year-over-year in the first half. Moving forward, as we scale our infrastructure to capture surging demand, this powerful capital efficiency will directly drive margin expansion and superior shareholder value. Overall, the continued expansion of the gene-to-protein platform, rapid growth in AIDD-driven demand, and improving returns on our platform investments underpin LSG's high-quality growth over the next several years. Turning to ProBio. The business continued its strong momentum in the first half, delivering revenue growth, improved profitability, and greater operational efficiency under our end-to-end CRDMO platform strategy. Please note that all the year-over-year growth rates presented here are on a comparable basis, excluding the financial impact of the LaNova license transaction. Revenue reached $61.1 million, up 34.2% year-over-year, continuing the healthy trend of recent quarters, driven by faster order execution, new customer wins, and progress across existing programs. More importantly, that growth is now translating into profitability. Adjusted gross profit reached $8.3 million, up substantially from around $0.7 million in first half 2025. Expanded project mix, higher utilization, and manufacturing efficiency all came through. Expense growth remained well below revenue growth. We kept investing in R&D and our technology platforms while tightening organizational efficiency. As revenue scaled, fixed costs absorbed more effectively. Operating leverage is now clearly visible. This show up most clearly in adjusted EBITDA, where the loss narrowed to $6.5 million from $16.8 million in first half 2025, an improvement of over $10 million and a meaningful step toward profitability. The investments we've made in platforms, global expansion, and capacity are now converting into profitability as revenue grows. Looking ahead, we will stay disciplined on high-quality growth, driving revenue, improving operating leverage, and reinforcing ProBio as a leading global CRDMO partner. Beyond revenue and margin, we are focused on the quality and the sustainability of future growth. On that front, our order intake stood out. On revenue, ProBio grew 34.2% organically. Biologics business grew 44.2%, and advanced therapy business grew 16.3%. Broad-based strength across both lines. The real headline is orders. New orders grew 54% year-over-year, significantly outpacing revenue growth. Biologics business up 62.1%, and advanced therapy business up 34.9%. Our backlog continued to build, further enhancing the visibility of our future revenue. By region, we achieved steady growth across all major markets. On revenue, China grew 43.1%, and international markets grew 30.3%. On orders, China grew 73.8%, and international markets grew 55.3%, demonstrating robust demand across both markets and solid BD outcomes. Overall, ProBio is delivering strong growth across revenue, new orders, and market expansion. In particular, orders consistently outpacing revenue reflects customer recognition of our end-to-end CRDMO platform. That reinforces our confidence in growth outlook ahead. Finally, turning to Bestzyme. Despite market headwinds, Bestzyme maintained a steady growth while continuing to invest in innovation and commercial execution. Revenue reached $30.4 million, up 7.4% year-over-year, driven by rising demand for core products and a growing customer base. Our expertise in industrial enzyme and biomanufacturing continues to reinforce our competitive position. Profitability also improved. Adjusted gross profit grew 14% year-over-year to $13 million, outpacing revenue growth on better product mix and improved manufacturing efficiency. Innovation remains our core driver, with adjusted R&D investment reaching $5.6 million in the first half, spending industry enzymes, biomanufacturing, and synthetic biology, while we apply AI and digital tools to improve R&D productivity and speed commercialization. Alongside that, we continued strengthening our commercial capabilities and global reach, expanding customer reach as demand grows for high-performance enzyme products and sustainable solutions. On the bottom line, adjusted operating loss was $1.3 million compared to a $0.6 million loss in first half 2025. A deliberate investment in platform and innovation that positions us to unlock larger growth ahead. Looking forward, with new product commercialization, continued market expansion, and emerging scale benefits, we expect Bestzyme to lift both revenue and profitability. To conclude, let me share our outlook for the full year. Looking ahead, we are actively capitalizing the industry tailwind, the acceleration of AI-driven Drug Discovery revolution, the fast expansion in global biopharma R&D, and the next generation transformation of global biomanufacturing. In Life Science Group, our mandate is clear. We will scale our leading gene synthesis platform solutions from sequence to data delivery with unmatched speed and capacity. We will keep digitalizing and automating our global lab network to improve efficiency and reliability. More importantly, we will be directly integrating our One Lab validating engine into our customers' R&D systems and digital infrastructure to power the future of AI drug discovery. In ProBio, we will continue to benefit from growing biologics demand and emerging opportunities in in vivo CAR-T and AIDD. We will expand our global footprint, strengthen our platforms, advance more programs from early discovery into clinical and commercial stage, and stay on track for positive EBITDA in 2027. In Bestzyme, we will focus on commercializing Sweet Protein, accelerating AI-enabled R&D and product optimization, and continuing to expand globally while strengthening our IP position. Supported by our strong first half performance and confidence in the opportunities ahead, we are raising our full-year guidance for the Life Science Service segment. We now expect revenue growth of 25%-30%, adjusted gross margin above 55%, and adjusted operating margin above 25%. For ProBio, we are increasing our revenue growth guidance to 25%-30% and continue to expect the business to achieve positive EBITDA in 2027. For Bestzyme, we expect revenue growth of 8%-10% while maintaining an adjusted gross margin of over 43%. Taken together, our platform leadership and continued investment in global reach and innovation positions GenScript to deliver high-quality growth and long-term shareholder value. That concludes today's presentation. Operator, please open the floor for questions. Thank you. As a reminder, to ask a question on your telephone, please press star one one and wait for your name to be announced. Just a moment for our first question, please. First question comes from the line of Yang Huang from JP Morgan. Please go ahead. Thanks for the opportunity to ask questions. I have two questions. I will first ask first one, then a follow-up. We noticed a significant upward revision to your 2026 guidance for the life science segment compared with the outlook provided early this year. Could management discuss the key drivers behind this upgrade and the relative contributions from different areas like AIDD-related demand, customer expansion, and project volume growth? Also, if we look ahead, given AIDD demand remain very strong, how should we think about the likelihood of further upside to the current life science guidance? Are you seeing any signs that such demand from AIDD will continue to outpace your existing assumptions? Thank you. That's the first one. Thank you, Yang, for your questions. I am happy to answer. This is Ray from GenScript Life Science Group. According to your questions, let me answer in this way. There were three things that drove our growth, and they reinforce each other rather than standing alone. First, the AIDD demand itself. As more AI-related biotech foundation model developers and innovation-focused pharma groups scale their investment in AI-enabled discovery, we are seeing strong growth from gene synthesis to protein expression and candidate validations, especially in the sequence-to-data generation solution that we tailored specifically for AIDD. Project sizes are increasing, and engagements are becoming deeper and more strategic. Both are showing up directly in order value and revenues. Second, our customer base is compounding and getting higher quality. We are winning new AI-focused accounts while maintaining the healthy demand from our traditional pharma and biotech base. More importantly, a growing share of customers are converting from single-project work into multi-stage, multi-service partnerships, which is what turns one-time projects into recurring revenue as partnerships. Third, we are now reaping the fruits of our years of platform investment. Sustained spending on automation, high-throughput capacity building, and digitalization is translating into shorter turnaround, higher utilization, and greater scalability. That operational leverage has become foundational to how fast we can further grow. For the second part of your question, we do believe AIDD is still early, and customers are moving from proof of concept into large-scale validation and iterations and optimization. That is exactly the phase where demand for high-throughput gene-to-protein productions and high-quality data accelerates. We are seeing that in three concrete signals. The sizes of the order are growing, the customers' relationships are deepening, and the share of high complexity and structured recurring orders, an area that we are uniquely strong, is rising. That last point matters most because it is what gives us confidence and visibility for long-term rather than just momentum. Just wanted to be clear, this growth is not the result of one larger customer or one project. It reflects a structural shift in demand and our unique ability to convert that demand into revenue and profitability at scale. Looking ahead, we are continuing to manage guidance prudently. However, the underlying demand signals project volume, size of the order, customer depth, and the growing mix of complex recurring AIDD projects are all pointing the same direction. Big pharmas are evolving and also adapting as well. So it is a fascinating time in the industry. If these trends continue and our unprecedented execution remains strong, and we are confident about that too, then we will see a real potential for continued upside versus our current assumptions. Thank you. Okay, great. Yeah, great. Thanks for the answer. My second one is on competitive landscape. To our understanding, Twist Bioscience is one of our company's primary competitors in the gene synthesis market. How does management view the competitive landscape between Twist and GenScript in the AIDD space related business? Thank you, Yang, for your question. Again, this is Ray. I would like to be a little bit more specific here because we think the data speaks for itself. At GenScript, we don't compete on commodity volume. We compete on value per delivered results, the speed to data, and the data quality that customers can actually rely on. Let me give you some numbers behind that. First, on economics, GenScript captured more than twice the revenue per delivered item versus the company you mentioned, and that gap has continued to widen. On throughput, we're processing, in real, more than 4,000 designs per day, meaningfully ahead of the publicly reported numbers from the company that you just mentioned, which is in thousands per week. The third, about speed. We deliver from digital sequence to binding data in four to seven calendar days, depending on which expression route the customer is taking. Comparing to more than two weeks reported somewhere in the market from the company you mentioned. The number is important here because this is three to five times faster iteration cycle, which matters enormously for customers who are doing AI model, depends on the continuous experimental feedback in the loop. We think the most important edge actually is the data quality. In one recent customer round evaluation, our assay variability came in under 10%, compared to close to 30% for the company that you mentioned in their workflow. So in the AIDD area, reliable, low variable data is not a nice-to-have, it's a must-to-have. That's where we believe our uniquely strong and clear advantage is most durable. I can explain a little bit more about our fundamental business model differences as well, by comparing the company you mentioned. Much of the competitive landscape, especially, they stop just at DNA or fragments. They couldn't go over. We deliver the full pass from sequence through to expression, to model-ready data reliably, at scale, with speed. We have already built critical downstream capabilities that close the loop end to end. Our infrastructure is built differently, too. We built modular, intelligent workstations rather than large, fixed format systems. This allows us to add capacity faster with meaningfully lower capital intensity. Eventually, we're targeting doubling the throughput of our capacity every quarter, and we have the competence to do that. We have to sustain in the industry-leading pace. That's what we have been committing to. Looking ahead, our objective is crystal clear. Serving the customers to be the definitive and always industry-leading biology validation engine, especially for the AI drug discovery era. Engineered for the speed, the scale, and reliability the industry now demands and requires. We mean to stay there. Thank you, Yang, for your question, and allowing me to have the opportunity there to explain. Thank you. Okay. Yeah, thank you, Ray, for the detailed explanation. Yeah, I finished my questions. Thank you, again. Thank you very much. Just a moment for our next question, please. Next, we have David Shang from Jefferies. Please go ahead. Can you hear me? Yeah. Thanks for taking my question. My first one is about your ProBio. We noticed that ProBio has begun securing AIDD projects in the first half of 2026. Could you please briefly discuss the current pipeline of drug discovery-related orders and the ProBio technology capability? My second question is about, we found both Life Science Service and the CDMO all has delivered the meaningful acceleration in the growth. Could the management elaborate on this capital allocation and CapEx plans to support this opportunity, and also to investors, we expect any incremental financing requirements or fundraising activities as company continues to expand its capacity and capability. Thank you, David. For the first question, Allen will help address, and for the second one, I am happy to address your questions. Thank you for your question, David. This is Allen of ProBio. For the first half of 2026, ProBio totally signed $ 9.7 million AIDD-related orders, including both for discovery and also CMC product. We delivered around $2.5 million revenue. The AI-generated drug candidate presents a unique development requirement and increasingly demands integrated solutions across discovery and also development. Based on our experience with the AIDD programs to date, there are several common characteristics. First, drug candidates generated or optimized by AI are typically complex molecules, including bispecific or trispecific antibody, which require further validation and optimization to address developability and drugability consideration. Second, the target selection and therapeutic application are becoming increasingly diverse, spanning multiple disease areas and modalities. Third, customers typically require significantly accelerated development timelines to maximize the efficiency advantages delivered by AI-driven discovery. Fourth, some customers will advance multiple candidate molecules simultaneously, and this creates demand for high throughput and also parallel development capability. To address this need from AIDD, ProBio has quickly established specialized solutions across both the discovery and CDMO value chain based on our extensive experiences, know-hows, and platforms. First, leveraging our more than 20 years experience in the biologics discovery segment, ProBio Discovery provides a comprehensive wet lab validation platform designed specifically for AIDD program. The key capabilities include customized data generation and experimental support for AI model training and optimization. Second, highly automated and high throughput workflows capable of processing thousands of samples per day. Third, integrated enrichment and readout pharmacology platform across multiple assay formats. Fourth, tailored screening strategies that optimize both biological activity and developability. Through this end-to-end approach, ProBio can help customers advance AI-generated candidate to PCC within as little as four months. Secondly, for our biologic CMC platform, we have introduced a combined developability assessment and Express CMC offering tailored for AI-derived molecules. The key advantages include early-stage developability assessments leveraging the same host cell system and expression vectors employed in downstream CMC development, and rapid identification of sequence liabilities and potential CMC challenges before entering formal development, meaningful reduction of downstream technical and manufacturing risks. We expanded our accelerated development framework beyond monoclonal antibody, symmetric bispecific antibody to include asymmetric bispecific, trispecific antibody, and also high concentration programs. For even the most challenging molecule formats, ProBio can progress from cell transfection to toxicology batch production in as little as 4.5 months, significantly shortening the development timeline for AI-driven programs. AIDD is really moving incredibly fast. With ProBio's extensive experience, competitive host cell line system, and integrated discovery and CMC platforms, we believe ProBio is well-positioned for AIDD program and will continuously capture this strategic opportunity. Thank you, Allen. David, for your question regarding our capital allocation and CapEx plans, we will keep investing into match this growth, not just chase it. Expanding capacity, automation, and the technology platforms to support the robust growth of both of LSG and the CDMO business. Our approach to capital allocation stays very disciplined throughout, and with every investment calibrated tightly to customer demand and expected return. Let me give you some numbers. During the first half of 2026, the group incurred a capital expenditure of $48.4 million. Based on current business momentum and the project execution progress, we expect full year 2026 CapEx to remain at a healthy and flexible level, with total CapEx approximately $130 million. Importantly, the company continues to maintain a robust balance sheet and a healthy liquidity structure. We currently hold approximately $830 million in cash and cash equivalents. In addition, our disciplined management of capital expenditure, operating costs, and the return on invested capital, ROIC, has driven a significant year-over-year improvement in both working capital and free cash flow during the first half of 2026. Given our substantial cash position, our continued ability to generate operating cash flow and a high-quality enterprise credit standing, we are confident that we have sufficient financial resources to support all ongoing expansion initiatives. Therefore, we do not view growth and investment as competing priorities. Our objective is to continue investing aggressively in the highest return opportunities while maintaining disciplined capital allocation and creating long-term shareholder value. Going forward, we will keep advancing our growth strategy with the same financial discipline and governance here. Importantly today, we are doing so from a position of increasing profitability, improving return on capital, and growing financial strength. To directly address your second question, we have a sufficient liquidity buffer, we see no need for equity financing. Thank you, David. Thank you. Thank you. Just a moment for our next question, please. Next we have Lawrence Chan from Morgan Stanley. Please go ahead. Thank you. First of all, congrats to management on these fantastic results. I have two questions. The first one is that within the AIDD customer base, we have noticed that large AI model companies are gradually becoming a new source of revenue growth. Could you help us better understand the profile of these customers and how their needs differ from those of traditional pharma and biotech companies? That's my first question. Thank you, Lawrence. This is Ray from GenScript Life Science Group again. It's a really interesting question, and we're learning as well along the way. As this is one of the most important shifts that we're seeing in our customer base, and it's worth being precise about what we have learned and how differently these customers behave. Let me start about the scale. A traditional pharma program typically advances a handful of candidates through a small number of projects, but the AI-native customers operate on an entirely different order of magnitude, and their models can generate hundreds, thousands of candidate sequences in a single iteration. And each of those needs rapid experimental validation. That alone changes the order size meaningfully. Second, about speed. It's truly different. A traditional design test to learn cycle runs in months. AI-native customers need a continuous fast feedback loop because the model requires a steady stream of experimental data to retrain and improve, which is why turnaround measures in days now and not weeks. High-throughput expression, automated platforms, it's must-have for those customers. Third, it's about the molecular complexity, and it's different. The traditional pharma projects concentrate heavily on well-validated targets or formats. AI-native customers, they are pushing the boundaries. They have more complex designs, and because the models are explicitly designed to explore molecular space that traditional discovery won't even attempt. So here's the insight that matters most, we think, how we will further grow. For AI-native customers, we're not just delivering a DNA construct or protein itself, we are delivering the data. The data is the end goal. The expression functional activity, binding stability, developability data, all feed back into the model development as input. This means we're not just selling one project or a deliverable. We're becoming part of the customer's AI development infrastructure, which is truly fascinating. That's what's driving the real upside, so that the customer lifetime value. The traditional engagement is often that one-off project. With AI-native relationship, can expand the complete workflow in drug discovery, which can also further extend to the clinical and CMC, like Allen just mentioned with ProBio. This is always one partner. Simply put, AI-native customers that demand more scale, more speed, more molecules, more designs, more data earlier in the process than traditional programs ever did. The companies that build for the high throughput, automated, end-to-end sequence to data, quality data delivery are the ones positioned to capture the value. That's exactly the infrastructure we have been building for the past two decades, and we build around this for success. More importantly, which is more exciting as well, the traditional pharma is evolving as well. They're adapting together along the way. So this is why we see the customer segment as a structural, a long-term growth driver rather than a short-term momentum. Thank you for allowing me to share what we have learned. Thank you, Ray. My second question is on Bestzyme. Bestzyme has been extensively integrating AI technologies into its operations under the AI for Science initiative. Could management provide more details on how AI is being applied at Bestzyme and the impact it's having on the business? Thank you, Lawrence, for the question. This is Aixi from Bestzyme. AI has become deeply integrated into every stage of R&D at Bestzyme. The business impact comes down to two things: faster R&D at a lower cost. First, our trained and fine-tuned models let us optimize enzyme performance across multiple dimensions. The enzyme molecules we are getting, say, performance levels that our old method simply could never reach. Second, our AI-driven Multi-property optimization has doubled our positive hit rate compared to 2025. In the best cases, we can hit our project goals in just two rounds of wireframe design with fewer than 150 mutants. This not only improves our project success rate, but also significantly increases the number of projects we deliver. For 2026, we expect to deliver six to seven projects, which is twice as many as in 2025. Third, we will shorten development cycles. We will launch both design online platform and the product flow agent platform. They are already cutting our lead time by 20%, and on top of that, the agent platform lets more of our scientists design and optimize enzymes simply by using natural language. It is much more accessible to the team. Fourth, our protein AI models help boost enzyme activity, while our gene-related models help improve our production yields. Put together, they drive significant cost reduction. Over the past year or two, we have seen meaningful cost savings across more than three projects. Take our PHI and high-temperature amylase as examples. Both achieved better performance at a lower cost, with gross margins up by 7% and 6%, respectively, for those single products. Thank you, Lawrence. Thank you. Just a minute for next question, please. Next, we have Linhai Zhao from Goldman Sachs. Please go ahead. Thanks for taking my question. Congrats on the great results for Life Science Group in particular. I am interested to get more color on the improved gross profit margin, in the first half. It seems like the AIDD orders came with a higher margin compared to the traditional gene-to-protein orders. Can management share more colors on that? Given that, can we get a better sense on moving forward, how should we think about the long-term AIDD margins? If the AIDD margins would likely to remain higher, how should we think about the entry barriers into this field and the competitive mode of GenScript? Also, Dr. Chen also mentioned that increasing utilization to cope with the demand as we are expecting triple-digit growth in the second half and even beyond. What is the utilization rate that we are currently seeing, and how are we preparing for the increased capacity going forward, especially for protein sides? I understand that the automation level is lower compared to the gene part. Thanks. Thank you, Linhai. This is Phil. I will address your first question regarding the profitability of AIDD orders. For the second part, utilization, I will defer to Ray to answer. AIDD-related orders carry structurally higher margin than traditional protein expression work. It is worth explaining exactly why, because the drivers are durable, not one time. First, customers typically face large-scale, high-volume orders, which significantly increase the protein expression throughput per project, and that is a portion of the fixed cost across our platform. Second, they normally pay a premium for speed. Rapid turnaround is not optional for them because their AI models depend on faster experimental feedback to keep iterating, and speed and scale is exactly what our automated high-throughput infrastructure is built to deliver. Third, and most important, the deliverables item itself is different. Customers are not just buying a protein. They are buying high-quality structured experimental data that feeds directly back into their models. There is a higher-value service than materials alone, and it commands the pricing accordingly. Put together, these three factors are why AIDD-related projects run roughly 20 percentage points higher in gross margin than traditional protein expression orders. Regarding your question on sustainability, we believe these differential holds and could widen for two reasons. One, the value we are pricing for it, that is the speed, scale, and model-ready data, as Ray just mentioned, becomes more variable and as AI adoption in drug discovery deepens, and because of cost of validation bottlenecks only grows more painful for customers as their models scale. Second, as our platform utilization increases and automation investments mature. Our own cost structure improves the apparel, which means we can defend this margin premium even as the category grows and the competitive intensity increases. That is a foundational and a structural advantage tied to how our base distributes and built to last. For the second one? Yes, thank you for your question. I can talk with you for days about how we could scale. The throughput is not only the genes, but also all the way to protein expression and the further downstream assays for the validations. Our throughput, our infrastructure, is built, as I mentioned, modular and intelligent workflows and workstations, which allows us to scale very rapidly with confidence. The orders, the magnitude that we are getting, no one else in the world could accept and deliver. That is what we are doing right now. We have the confidence to further doubling our throughput capacities in the coming days and coming months, in a very exciting way. Thank you. Thank you. Thank you very much. Yeah. Thank you for your interest and the questions and the ongoing support for GenScript. We apologize for not being able to address all the questions due to time limitations. If you have additional questions, do not hesitate to reach out to our investor relations team. We will see you on our next call. Thank you. This concludes today's conference call. Thank you for participating. You may now disconnect.